何のコーパスか: カメラの雑音(EMVA 1288)・ISP・HDR・LED のちらつき・レンズのフレアと周辺減光・ローリングシャッター・モーションブラー、LiDAR の強度と入射角・霧と降雪の減衰、レーダーの伝搬とドップラー、センサー模擬の検証。
Fullseye でなぜ要るか: 自前の世界の描画を物理で根拠づけるための知識。各効果は閉形式の門が立つ(cos⁴ 減光・PTC の傾き・Koschmieder・LiDAR 方程式)ので、CARLA の写実と比べる前に Fullseye 側の正しさを固められる。
来歴: OpenAlex から取得した論文メタデータ 704 本(2012 年以降、fetch_openalex_topical.py)を TF-IDF + k-means で 56 クラスタに階層化し(raptor の corpus2skill、2026-10-03)、各クラスタの要約を LLM(claude-haiku-4-5)が書いた。ここに載せるのはその要約と、代表論文の題名・著者・年・DOI だけ(メタデータは CC0。抄録は出版社の権利なので写さない)。要約は生成時の英語のまま。正直な限界: 文献は原理・選定・校正の研究が中心で、型番やデータシートの数値(製品知識)は薄い。
使い方(op に落とす): 各クラスタの「使う op」は、知識のテーマ → op の対応表(tools/gen_literature_notes.py の THEME_OPS、人が書いたもの)で引いた実在の op(生成時に出荷ノート 3,623 本の一覧と突き合わせ、無ければ止まる)。op の後ろはなぜ使うかと型。テーマに当たらないクラスタは「op に落ちていない」と書く(Fullseye に無い領域を隠さない)。読む順: 工程・部品の話題 → クラスタ → 使う op → op ノート(型の契約・実行できる例)→ 実装。末尾の「op → クラスタ」で逆に引ける。
22 本
This cluster is largely off-topic for driving sensor simulation: it gathers visible light communication (VLC/Li-Fi), optical camera communication (OCC) and visible light positioning work, including vehicular VLC and LED-based patient monitoring. Its relevance to sensor simulation is indirect but real: the same LED pulse-width modulation, rolling-shutter stripe capture and ambient-light noise that VLC exploits are what cause LED flicker artefacts in automotive cameras.
使う op(テーマ → op の対応表から。ノートで型と例を確かめてから使う):
Introductory and survey-style papers on Li-Fi: data transmission through LED lighting, cell coverage design for Li-Fi access points, energy aspects, and a Li-Fi-based vehicle collision avoidance concept.
Reviews and systems for visible light positioning and optical camera communication, including vehicular VLC channel models, OCC-based vehicle positioning in V2I settings, smartphone LED decoding, pixel-level VLC projectors and LOS-blockage mitigation.
Hardware-level VLC and OCC work: Manchester-OOK transceivers, tuned analog front-ends to extend range under ambient light, exposure synchronisation for time-division OCC, and the trade-off between flicker, data rate and bit error rate.
A single performance study comparing visible-light and ultraviolet optical wireless links, including non-line-of-sight operation where UV relies on atmospheric scattering.
95 本
A mixed cluster. One coherent part covers LiDAR radiometry: correcting terrestrial, airborne and hyperspectral LiDAR intensity for range, incidence angle and temperature so it becomes a reflectance-like quantity.
使う op(テーマ → op の対応表から。ノートで型と例を確かめてから使う):
koschmieder(視程と消散係数(Koschmieder)、any × any × scalar × any → any)、beta_from_mor(気象光学距離 → 消散係数、scalar → scalar)、fog_beta_from_profile(画像の明るさの縦断から霧の濃さ、any × any × scalar × scalar × scalar → table)、veiling_luminance(まぶしさの光幕輝度、any × any → any)、sight_stop_speed(見える距離で止まれる速さ、scalar × scalar × scalar → scalar)、env_params(天候の母数、入力なし → table)lidar_spec(走査の仕様、入力なし → table)、lidar_scan(世界を走査、mesh × table × matrix → table)、ray_plane_range(平面までの距離(閉形式)、points × points → signal)、ray_box_ranges(箱までの距離(閉形式)、points × points → signal)、project_spherical(球面投影、points → image2d)、tof_multipath_phase(凹みの多重反射で ToF の位相がずれる量(閉形式)、入力なし → table)、tof_transport_depth(輸送行列で多重反射を入れた ToF の深度、table → table)world_build(コースから 3-D の世界、table → table)、world_camera(色・ラベル・深度・面番号を一度に、table × matrix × matrix → table)、world_move(物体を動かす、table → any)、env_render(太陽・霧・雨・夜、table × matrix × matrix → table)、tile_stream(終わらない地図、table × table → table)、gs_from_world(世界 → 3DGS、table → table)、carla_scene_world(CARLA の場面を自前の世界に(同じ場面を両方で)、table → table)、carla_depth_decode(CARLA の深度画像(RGB 符号)を m に、rgb → image2d)、carla_transform_matrix(CARLA の座標系(左手・度)↔ 自前の行列、any → matrix)、cr_read(CommonRoad のシナリオ XML を読む、any → table)、cr_drive(CommonRoad のシナリオを運転して採点、table → table)、osm_road_graph(OSM の道路網から地図、table → table)Fluid-dynamics studies of drops and precipitation: wind-induced deflection of hydrometeors around gauges and disdrometers, drop impact and wetting simulation, anti-icing surfaces, automotive surface contamination, a bus side-slip/rollover study in rain, snow and crosswind, and a direct-detection Doppler wind lidar.
koschmieder(視程と消散係数(Koschmieder)、any × any × scalar × any → any)、beta_from_mor(気象光学距離 → 消散係数、scalar → scalar)、fog_beta_from_profile(画像の明るさの縦断から霧の濃さ、any × any × scalar × scalar × scalar → table)、veiling_luminance(まぶしさの光幕輝度、any × any → any)、sight_stop_speed(見える距離で止まれる速さ、scalar × scalar × scalar → scalar)、env_params(天候の母数、入力なし → table)Radiometric calibration and correction of terrestrial and airborne laser-scanner intensity: incidence-angle and distance effects, reference-target methods, temperature compensation, full-waveform reflectance, and applications such as road-marking extraction, beach moisture and material classification.
lidar_spec(走査の仕様、入力なし → table)、lidar_scan(世界を走査、mesh × table × matrix → table)、ray_plane_range(平面までの距離(閉形式)、points × points → signal)、ray_box_ranges(箱までの距離(閉形式)、points × points → signal)、project_spherical(球面投影、points → image2d)、tof_multipath_phase(凹みの多重反射で ToF の位相がずれる量(閉形式)、入力なし → table)、ほか 1 個: tof_transport_depthAtmospheric science on precipitation and clouds observed by spaceborne radar and lidar (CloudSat, CALIPSO, EarthCARE): snowfall climatology over Greenland and Antarctica, ice- versus liquid-phase precipitation, microphysics schemes, and high ice water content at low reflectivity.
koschmieder(視程と消散係数(Koschmieder)、any × any × scalar × any → any)、beta_from_mor(気象光学距離 → 消散係数、scalar → scalar)、fog_beta_from_profile(画像の明るさの縦断から霧の濃さ、any × any × scalar × scalar × scalar → table)、veiling_luminance(まぶしさの光幕輝度、any × any → any)、sight_stop_speed(見える距離で止まれる速さ、scalar × scalar × scalar → scalar)、env_params(天候の母数、入力なし → table)Fog and low cloud: occurrence and temperature inversions, infrared fog detection, cloud radar and in-situ microphysics of fog, ship-based lidar evaluation of models, and polarised-light persistence through fog.
koschmieder(視程と消散係数(Koschmieder)、any × any × scalar × any → any)、beta_from_mor(気象光学距離 → 消散係数、scalar → scalar)、fog_beta_from_profile(画像の明るさの縦断から霧の濃さ、any × any × scalar × scalar × scalar → table)、veiling_luminance(まぶしさの光幕輝度、any × any → any)、sight_stop_speed(見える距離で止まれる速さ、scalar × scalar × scalar → scalar)、env_params(天候の母数、入力なし → table)Incidence-angle effects in multispectral and hyperspectral LiDAR backscatter, mainly for vegetation, leaves and coastal surfaces: radiometric calibration against range, angle and sub-footprint effects, and the impact of intensity normalisation on derived products such as leaf area index.
lidar_spec(走査の仕様、入力なし → table)、lidar_scan(世界を走査、mesh × table × matrix → table)、ray_plane_range(平面までの距離(閉形式)、points × points → signal)、ray_box_ranges(箱までの距離(閉形式)、points × points → signal)、project_spherical(球面投影、points → image2d)、tof_multipath_phase(凹みの多重反射で ToF の位相がずれる量(閉形式)、入力なし → table)、ほか 1 個: tof_transport_depthSnowfall observation and modelling: airport weather hazards with low visibility, snowfall impact on albedo and snowmelt, lake-based snowfall measurement, snow density from collocated disdrometer and Micro Rain Radar, and microwave radiative transfer of a snowfall event.
world_build(コースから 3-D の世界、table → table)、world_camera(色・ラベル・深度・面番号を一度に、table × matrix × matrix → table)、world_move(物体を動かす、table → any)、lidar_scan(同じ世界の LiDAR、mesh × table × matrix → table)、env_render(太陽・霧・雨・夜、table × matrix × matrix → table)、tile_stream(終わらない地図、table × table → table)、ほか 13 個: gs_from_world、carla_scene_world、carla_depth_decode、carla_transform_matrix、cr_read、cr_drive、osm_road_graph、koschmieder、beta_from_mor、fog_beta_from_profile、veiling_luminance、sight_stop_speed、env_paramsLiDAR signal modelling beyond automotive: full-waveform simulation for incidence angle and ranging accuracy, intensity correction for pulsed LiDAR, Monte Carlo polarised propagation in dense media, underwater single-pixel imaging, nacelle wind lidar motion correction, vector-vortex beams and a railway LiDAR simulator in Unreal Engine.
lidar_spec(走査の仕様、入力なし → table)、lidar_scan(世界を走査、mesh × table × matrix → table)、ray_plane_range(平面までの距離(閉形式)、points × points → signal)、ray_box_ranges(箱までの距離(閉形式)、points × points → signal)、project_spherical(球面投影、points → image2d)、tof_multipath_phase(凹みの多重反射で ToF の位相がずれる量(閉形式)、入力なし → table)、ほか 1 個: tof_transport_depthSnow hydrology and glaciology: snow accumulation and redistribution (including terrestrial laser scanning of a steep rock face), modelling mountain precipitation, avalanche forecasting, gridded snow-depth datasets and blowing-snow simulation.
koschmieder(視程と消散係数(Koschmieder)、any × any × scalar × any → any)、beta_from_mor(気象光学距離 → 消散係数、scalar → scalar)、fog_beta_from_profile(画像の明るさの縦断から霧の濃さ、any × any × scalar × scalar × scalar → table)、veiling_luminance(まぶしさの光幕輝度、any × any → any)、sight_stop_speed(見える距離で止まれる速さ、scalar × scalar × scalar → scalar)、env_params(天候の母数、入力なし → table)140 本
Camera image formation and its degradations: RAW noise and image signal processing (ISP), high dynamic range capture and tone mapping, LED flicker in HDR automotive sensors, lens flare and veiling glare, motion blur, and rain/raindrop artefacts. Covers both physically based simulation of these effects and learned removal, with several automotive-specific papers on sensor and ISP tuning for detection.
使う op(テーマ → op の対応表から。ノートで型と例を確かめてから使う):
aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、emva_dynamic_range(ダイナミックレンジ、入力なし → table)、raw_demosaic_bilinear(デモザイク、image2d → rgb)、tone_map(階調、any × scalar → any)、estimate_noise(雑音の推定、image → feature)、noise_sigma(雑音の標準偏差、image2d → measurement)deflicker(ちらつきの除去、video → video)、flash_frequency(点滅の周波数、signal → table)、aliased_frequency(フレームレートとのエイリアシング、any → any)gs_from_world(メッシュの世界 → ガウス、table → table)、gs_render(ガウスの描画、table × matrix → table)、gs_update(ガウスの更新、table × table → table)、gs_read_file(3DGS の読み込み、入力なし → table)、humanoid_impostors(向き × 位相の事前描画(安い代替)、table → table)aug_rolling_shutter(ローリングシャッター(斜線の傾き = v·t_line)、image → image)、aug_motion_blur(モーションブラー(スペクトルの零点)、image → image)、xkor_motion_blur(第 2 実装のブラー、image → image)aug_vignette(cos⁴ の周辺減光、image → image)、vignette(周辺減光、rgb → rgb)、distortion_map(歪みの地図、table → table)、psf_to_mtf(PSF → MTF、image2d → pairs)、sfr_from_edge(斜めエッジから SFR(ISO 12233)、table → pairs)、mtf50(解像の指標、pairs → measurement)、veiling_glare_index(ベールグレアの指数、image2d × image2d × image2d → table)Motion blur and image degradation estimation and removal: event- and gyro-assisted deblurring, parametric estimation of motion, defocus and turbulence blur, video deblurring for robots and vehicles, rain-streak removal, and blind noise-level estimation for sensor noise.
aug_rolling_shutter(ローリングシャッター(斜線の傾き = v·t_line)、image → image)、aug_motion_blur(モーションブラー(スペクトルの零点)、image → image)、xkor_motion_blur(第 2 実装のブラー、image → image)、aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、ほか 8 個: emva_photon_transfer、emva_dark_current、emva_spatial_nonuniformity、emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigmaHDR reconstruction and exposure strategy: multi-exposure fusion, adaptive auto-exposure in dynamic scenes, extreme low-light RGGB reconstruction, the modulo camera, backward-compatible HDR file formats, invertible ISP between RAW and sRGB, plus camera identification from optical defects and gain compensation across LiDAR-mounted panoramas.
gs_from_world(メッシュの世界 → ガウス、table → table)、gs_render(ガウスの描画、table × matrix → table)、gs_update(ガウスの更新、table × table → table)、gs_read_file(3DGS の読み込み、入力なし → table)、humanoid_impostors(向き × 位相の事前描画(安い代替)、table → table)、aug_shot_noise(光子の雑音、image → image)、ほか 13 個: aug_read_noise、emva_snr_curve、emva_photon_transfer、emva_dark_current、emva_spatial_nonuniformity、emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigma、deflicker、flash_frequency、aliased_frequencyImage signal processing for cameras, with emphasis on automotive and machine-vision use: ISP stage design and parallel hardware, application-driven automatic parameter tuning, CNN replacements for ISP, bypassing the ISP for detection, end-to-end optimisation of optics-sensor-ISP for driving, HDR linearity evaluation, blind RAW denoising with variance stabilisation, single-photon cameras and full image-system simulation.
aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、ほか 5 個: emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigmaLens flare, glare and other optical artefacts: real-time flare rendering via polynomial ray transfer and tile-based ghosts, flare removal datasets and networks for night driving, veiling glare synthesis, vignetting as an adversarial attack, projector-induced ghost attacks, raindrop detection reviews and rain generation, plus stereo image simulation for automotive validation.
aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、ほか 12 個: emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigma、aug_vignette、vignette、distortion_map、psf_to_mtf、sfr_from_edge、mtf50、veiling_glare_indexExposure control and HDR sensing hardware: noise-based HDR calibration, LDR vs HDR sky luminance, virtual exposure control for visual SLAM, FPGA smart cameras merging exposures, tunnelling photodiodes and dual-photodiode tone mapping, SPAD differential counting, multi-sensor HDR video, counterlight detection, contrast autofocus and converting RAW frames to events.
aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、ほか 8 個: emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigma、deflicker、flash_frequency、aliased_frequencyAutomotive HDR CMOS sensors and LED flicker mitigation (LFM): split-pixel and LOFIC architectures, triple-gain readout, 4-tap charge splitting, HDR synthesis, flicker detection in non-HDR video, the effect of flare on achievable dynamic range, and a physics-based radiance dataset for benchmarking LFM.
aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、ほか 8 個: emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigma、deflicker、flash_frequency、aliased_frequencyA small, loosely related group: reconfigurable industrial vision inspection, camera-based anti-facial-recognition by ISP tuning, age estimation robust to sensor variations, and PRNU-based image forensics.
Automotive camera image quality topics: adherent raindrop simulation and removal, tone mapping and demosaicing for driving, how camera parameters affect CNN generalisation, calibrated HDR of daylit scenes, polarisation- and spectral-filter-array HDR, spike and event cameras, plus a stray joint radar-communication paper.
aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、ほか 8 個: emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigma、deflicker、flash_frequency、aliased_frequency73 本
Perception sensor models for virtual testing of automated driving, with radar as the central example: fidelity classes from ideal object lists to ray-traced signal-level simulation, FMCW radar simulation frameworks, scattering-centre and RCS modelling with multipath, and methodologies for validating sensor models against real measurements (sensitivity analysis, on-road comparison, scenario design, XiL/HiL test benches).
使う op(テーマ → op の対応表から。ノートで型と例を確かめてから使う):
world_build(コースから 3-D の世界、table → table)、world_camera(色・ラベル・深度・面番号を一度に、table × matrix × matrix → table)、world_move(物体を動かす、table → any)、lidar_scan(同じ世界の LiDAR、mesh × table × matrix → table)、env_render(太陽・霧・雨・夜、table × matrix × matrix → table)、tile_stream(終わらない地図、table × table → table)、gs_from_world(世界 → 3DGS、table → table)、carla_scene_world(CARLA の場面を自前の世界に(同じ場面を両方で)、table → table)、carla_depth_decode(CARLA の深度画像(RGB 符号)を m に、rgb → image2d)、carla_transform_matrix(CARLA の座標系(左手・度)↔ 自前の行列、any → matrix)、cr_read(CommonRoad のシナリオ XML を読む、any → table)、cr_drive(CommonRoad のシナリオを運転して採点、table → table)、osm_road_graph(OSM の道路網から地図、table → table)fmcw_range_profile(FMCW の距離、beatcube → signal)、range_doppler_map(距離・速度の地図、beatcube → image2d)、doppler_shift(ドップラーの閉形式、any → any)、doppler_track(サイレンの周波数の追跡、signal → table)、tdoa_bearing(到着時間差から方向、signal × signal → table)ttc_truth(衝突までの時間の真値、image2d × matrix × matrix → table)、ttc_from_range(距離の列からの TTC、入力なし → scalar)、rss_longitudinal_check(RSS の縦の安全距離、table → table)、rss_lateral_check(RSS の横の安全距離、table → table)、dilemma_zone(黄信号のジレンマゾーン(閉形式)、any → table)、occlusion_safe_speed(死角から止まれる速さ、any → any)、turn_maneuver_check(右左折の採点、table → table)、skill_test_score(技能試験の減点、table → table)idm_platoon_simulate(IDM の車列、any → table)、idm_equilibrium_gap(IDM の定常車間(閉形式)、any → any)、driver_style(運転の癖を個体ごとに、入力なし → table)、lateral_wobble(車線内のふらつき、入力なし → signal)、lane_change_permitted(進路変更の可否、table → table)、passing_decision(すれ違いの判断、入力なし → any)、social_force_step(歩行者の Social Force、points × points × points → any)curvature_speed_plan(曲率から速度の計画、any → table)、pure_pursuit_curvature(pure pursuit、any → table)、stanley_steer(Stanley、any → table)、stop_line_plan(停止線までの計画、scalar × scalar → table)、long_simulate(縦の運動、scalar × scalar × any → table)、bicycle_model_step(自転車モデル、any → any)Virtual testing of ADAS/AD sensing: identifying performance limitations of sensing technologies, testing challenges in practice, radar model validation under non-ideal conditions, a geometric occlusion model, surround-view fisheye optics and their artefacts, visibility through rainy windshields, configurable sensor model architectures, an experimentally validated camera model and HiL testing approaches.
Radar sensor modelling for virtual validation: measurement campaigns that expose modelling challenges, real-time active perception sensor models, synthetic radar data generation, and simulating FMCW resolution limits for detecting vulnerable road users.
fmcw_range_profile(FMCW の距離、beatcube → signal)、range_doppler_map(距離・速度の地図、beatcube → image2d)、doppler_shift(ドップラーの閉形式、any → any)、doppler_track(サイレンの周波数の追跡、signal → table)、tdoa_bearing(到着時間差から方向、signal × signal → table)Methodology for credible perception sensor simulation: validating camera sensor models for vision systems, deriving logical-scenario design criteria from sensor-model requirements, a development method with continuous verification and validation, and first-principles 3D simulation to search SOTIF corner cases.
A broad set of works on environment-sensor simulation for testing automated driving functions: radar target stimulation, fast generic sensor models, reviews of perception testing, adverse-weather recognition, sensitivity analysis of radar simulation, collaborative requirements for credible sensor simulation, real-time LiDAR on vehicle-in-the-loop, benchmarking and functional decomposition of LiDAR models, physically correct windshield raindrops, RadaRays rotating FMCW radar, and modelling-fidelity issues.
Ray-tracing based radar and mmWave channel simulation: measurement-backed automotive mmWave ray tracing, ray metadata for efficient full-radar simulation with automatic annotation, image-rendering-based MIMO radar simulation, antenna-to-system full physics, physically based road-surface material parameters, scattering-centre extraction for traffic participants, and RCS radial patterns combined with analytic multipath.
fmcw_range_profile(FMCW の距離、beatcube → signal)、range_doppler_map(距離・速度の地図、beatcube → image2d)、doppler_shift(ドップラーの閉形式、any → any)、doppler_track(サイレンの周波数の追跡、signal → table)、tdoa_bearing(到着時間差から方向、signal × signal → table)Perception functions and abstract sensor models in automated driving: lane detection review, issues in traffic-light recognition, high-level sensor models for training driving policies, and LiDAR co-simulation for maritime assistance V&V.
idm_platoon_simulate(IDM の車列、any → table)、idm_equilibrium_gap(IDM の定常車間(閉形式)、any → any)、driver_style(運転の癖を個体ごとに、入力なし → table)、lateral_wobble(車線内のふらつき、入力なし → signal)、lane_change_permitted(進路変更の可否、table → table)、passing_decision(すれ違いの判断、入力なし → any)、ほか 7 個: social_force_step、curvature_speed_plan、pure_pursuit_curvature、stanley_steer、stop_line_plan、long_simulate、bicycle_model_stepFMCW radar simulation frameworks at signal level: photonic radar range-speed mapping, a 512-channel 4D imaging radar, ray tracing for large MIMO arrays, noise-aware and multipath-aware simulation, antenna-pattern effects, FMCW versus PMCW waveform evaluation, deep stochastic radar models, and a Blender-based channel simulator.
fmcw_range_profile(FMCW の距離、beatcube → signal)、range_doppler_map(距離・速度の地図、beatcube → image2d)、doppler_shift(ドップラーの閉形式、any → any)、doppler_track(サイレンの周波数の追跡、signal → table)、tdoa_bearing(到着時間差から方向、signal × signal → table)Simulation platforms and frameworks for automated vehicles and other autonomous systems: virtual-to-real ADAS prototyping, hybrid commissioning, autonomous ferries with EM-radiation sensors, RC-car validation, a survey of automotive radar modelling, interoperable sensor/vehicle/environment simulation, a standardised sensor-modelling framework, camera and LiDAR models, MVSim, ENABLE-S3, and the Japanese DIVP project on physics-based sensor models.
ttc_truth(衝突までの時間の真値、image2d × matrix × matrix → table)、ttc_from_range(距離の列からの TTC、入力なし → scalar)、rss_longitudinal_check(RSS の縦の安全距離、table → table)、rss_lateral_check(RSS の横の安全距離、table → table)、dilemma_zone(黄信号のジレンマゾーン(閉形式)、any → table)、occlusion_safe_speed(死角から止まれる速さ、any → any)、ほか 2 個: turn_maneuver_check、skill_test_score45 本
Rolling-shutter (RS) imaging: geometric distortion models and correction, RS-aware stereo, relative pose and visual-inertial odometry, continuous-time camera-IMU calibration, RS as a sensing mechanism (optical camera communication, speckle imaging, compressive video) and as an attack surface (adversarial LED stripes), plus RS effects in star trackers. One small leaf is unrelated astrophysics data.
使う op(テーマ → op の対応表から。ノートで型と例を確かめてから使う):
aug_rolling_shutter(ローリングシャッター(斜線の傾き = v·t_line)、image → image)、aug_motion_blur(モーションブラー(スペクトルの零点)、image → image)、xkor_motion_blur(第 2 実装のブラー、image → image)aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、emva_dynamic_range(ダイナミックレンジ、入力なし → table)、raw_demosaic_bilinear(デモザイク、image2d → rgb)、tone_map(階調、any × scalar → any)、estimate_noise(雑音の推定、image → feature)、noise_sigma(雑音の標準偏差、image2d → measurement)curvature_speed_plan(曲率から速度の計画、any → table)、pure_pursuit_curvature(pure pursuit、any → table)、stanley_steer(Stanley、any → table)、stop_line_plan(停止線までの計画、scalar × scalar → table)、long_simulate(縦の運動、scalar × scalar × any → table)、bicycle_model_step(自転車モデル、any → any)aug_vignette(cos⁴ の周辺減光、image → image)、vignette(周辺減光、rgb → rgb)、distortion_map(歪みの地図、table → table)、psf_to_mtf(PSF → MTF、image2d → pairs)、sfr_from_edge(斜めエッジから SFR(ISO 12233)、table → pairs)、mtf50(解像の指標、pairs → measurement)、veiling_glare_index(ベールグレアの指数、image2d × image2d × image2d → table)Rolling-shutter effects and exploitation in CMOS sensors: adaptive exposure to reduce RS artefacts, real-time and low-power RS compensation, RS stereo depth under motion, RS-induced aberrations in wavefront sensing, measuring propeller speed from RS distortion, compressive temporal imaging with RS arrays, RS-VLC security and an acoustic side channel through RS and lens motion.
aug_rolling_shutter(ローリングシャッター(斜線の傾き = v·t_line)、image → image)、aug_motion_blur(モーションブラー(スペクトルの零点)、image → image)、xkor_motion_blur(第 2 実装のブラー、image → image)、aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、ほか 8 個: emva_photon_transfer、emva_dark_current、emva_spatial_nonuniformity、emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigmaRolling-shutter modelling in vision and photogrammetry: a simulation framework for airborne camera imperfections, RS correction in uncalibrated video and with deep networks, UAV photogrammetric RS correction models and calibration error simulation, stereo RS relative pose, event-guided interpolation for RS frames, dual reversed-shutter HDR and RS speckle imaging for blood-flow measurement.
curvature_speed_plan(曲率から速度の計画、any → table)、pure_pursuit_curvature(pure pursuit、any → table)、stanley_steer(Stanley、any → table)、stop_line_plan(停止線までの計画、scalar × scalar → table)、long_simulate(縦の運動、scalar × scalar × any → table)、bicycle_model_step(自転車モデル、any → any)、ほか 3 個: aug_rolling_shutter、aug_motion_blur、xkor_motion_blurRolling-shutter stripe phenomena: optical camera communication decoding (DFT-based barcode detection, DCO-OFDM on smartphones, indoor positioning), stray-light analysis, and invisible adversarial attacks that use high-frequency LED modulation to inject stripes into traffic-sign images.
aug_rolling_shutter(ローリングシャッター(斜線の傾き = v·t_line)、image → image)、aug_motion_blur(モーションブラー(スペクトルの零点)、image → image)、xkor_motion_blur(第 2 実装のブラー、image → image)Off-topic: data-set records of astrophysical self-lensing simulations of white-dwarf binaries (with white-dwarf, neutron-star or black-hole companions) evaluated for various sky surveys.
aug_vignette(cos⁴ の周辺減光、image → image)、vignette(周辺減光、rgb → rgb)、distortion_map(歪みの地図、table → table)、psf_to_mtf(PSF → MTF、image2d → pairs)、sfr_from_edge(斜めエッジから SFR(ISO 12233)、table → pairs)、mtf50(解像の指標、pairs → measurement)、ほか 1 個: veiling_glare_indexRolling-shutter geometry for visual-inertial systems: an RS visual-inertial dataset, empirical identification of RS parameters, generalised epipolar geometry for RS relative pose, VINS with inaccurate timestamps, continuous-time camera-IMU spatiotemporal calibration, continuous-time RS VIO, and optimal flutter-shutter (coded exposure) theory.
aug_rolling_shutter(ローリングシャッター(斜線の傾き = v·t_line)、image → image)、aug_motion_blur(モーションブラー(スペクトルの零点)、image → image)、xkor_motion_blur(第 2 実装のブラー、image → image)Rolling shutter in space and specialised imaging: star sensor and star tracker RS distortion modelling and correction (including particle-swarm calibration and high-rate attitude updates), RS image motion in CMOS detectors, LED-strobe characterisation of a CubeSat camera, and lensless video from stills via RS.
aug_rolling_shutter(ローリングシャッター(斜線の傾き = v·t_line)、image → image)、aug_motion_blur(モーションブラー(スペクトルの零点)、image → image)、xkor_motion_blur(第 2 実装のブラー、image → image)167 本
Camera and image-sensor characterisation, calibration and measurement: EMVA 1288 photon-transfer methods, IEEE P2020 automotive image-quality metrics (noise, flicker, contrast detection probability), sCMOS noise, vignetting and distortion calibration, radiometric and spectral calibration, time-of-flight cameras, stray light and windshield optics. The cluster is noisy: a sizeable share is microscopy, materials or entirely unrelated papers swept in by keywords.
使う op(テーマ → op の対応表から。ノートで型と例を確かめてから使う):
aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、emva_dynamic_range(ダイナミックレンジ、入力なし → table)、raw_demosaic_bilinear(デモザイク、image2d → rgb)、tone_map(階調、any × scalar → any)、estimate_noise(雑音の推定、image → feature)、noise_sigma(雑音の標準偏差、image2d → measurement)deflicker(ちらつきの除去、video → video)、flash_frequency(点滅の周波数、signal → table)、aliased_frequency(フレームレートとのエイリアシング、any → any)aug_vignette(cos⁴ の周辺減光、image → image)、vignette(周辺減光、rgb → rgb)、distortion_map(歪みの地図、table → table)、psf_to_mtf(PSF → MTF、image2d → pairs)、sfr_from_edge(斜めエッジから SFR(ISO 12233)、table → pairs)、mtf50(解像の指標、pairs → measurement)、veiling_glare_index(ベールグレアの指数、image2d × image2d × image2d → table)Mostly low-light scientific imaging: back-illuminated sCMOS characterisation and noise correction for super-resolution microscopy, photophysical noise modelling, single-molecule simulation, plus integrated lens-degradation modelling (distortion, blur, vignetting), stray-light analysis of camera systems, lensless low-light imaging and long-exposure celestial attitude estimation.
aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、ほか 5 個: emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigmaA heterogeneous group around light sources, radiometry and sensor calibration: road lighting quality versus pavement reflection, photometric characterisation of road surfaces, an analytic automotive LiDAR simulation with blooming and ambient light, windshield optical impact on cameras, an automotive HDR sensor with LED flicker mitigation, simulation of automotive perception systems, radiometric calibration of DSLR, multispectral and thermal imagers.
tone_map(HDR の階調圧縮、any × scalar → any)、deflicker(ちらつきの除去、video → video)、flash_frequency(点滅の周波数、signal → table)、aliased_frequency(フレームレートとのエイリアシング、any → any)Calibration and surface-appearance topics: high-precision distortion measurement with a calibration harp, oblique multi-camera calibration, semantic self-calibration of vehicle cameras, stereo-LiDAR fusion, rain behaviour on hydrophilic and hydrophobic lens covers, HDR headlamp measurement, specular highlight streaks, specular defect detection and radar interference mitigation.
aug_vignette(cos⁴ の周辺減光、image → image)、vignette(周辺減光、rgb → rgb)、distortion_map(歪みの地図、table → table)、psf_to_mtf(PSF → MTF、image2d → pairs)、sfr_from_edge(斜めエッジから SFR(ISO 12233)、table → pairs)、mtf50(解像の指標、pairs → measurement)、ほか 1 個: veiling_glare_indexIndustrial imaging with HDR and appearance capture: HDR-based detection of split defects in sheet-metal stamping and in wire-arc additive manufacturing, sensor data modelling from optical properties of composites, polarisation-based molecular orientation microscopy and PBR material capture via photometric stereo.
Sensor and image correction methods: vignetting correction from measured luminance distribution or Gaussian models, temperature-induced noise correction, EMVA 1288 radiometric extension, spectral filter-on-chip angular dependence, polarisation sensor characterisation, radiation testing of COTS CMOS, RAW preprocessing effects on photogrammetric accuracy, built-in lens correction profiles, and multispectral UAV sensor correction.
aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、ほか 12 個: emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigma、aug_vignette、vignette、distortion_map、psf_to_mtf、sfr_from_edge、mtf50、veiling_glare_indexAutomotive image-quality standardisation and temporal light artefacts: reviews of IEEE P2020 flicker and noise metrics, psychophysics of LED flicker for digital mirrors, contrast detection probability and colour separation, stroboscopic and phantom-array effects of LED lighting, plus imaging LiDAR through fog and dust, ghost reflections in laser vibrometry and IEEE P4001 hyperspectral standards.
tone_map(HDR の階調圧縮、any × scalar → any)、deflicker(ちらつきの除去、video → video)、flash_frequency(点滅の周波数、signal → table)、aliased_frequency(フレームレートとのエイリアシング、any → any)Image sensor characterisation and emerging automotive sensors: EMVA 1288 implementations and light-source effects, camera models for tilt lenses, high-speed and scientific CMOS testing, event-camera characterisation and low-latency automotive event vision, VIS+NIR imaging for driving, the case for an LMS (cone-like) camera, computational radiometric/spectral calibration, LiDAR intensity-to-reflectance, ISP memory/efficiency and security of the camera pipeline.
aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、ほか 5 個: emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigmaOptical measurement and sensor-realistic simulation: time-of-flight camera acquisition, enhancement and multipath-aware AMCW simulation, time-gated rendering, fringe-projection precision models, camera dynamic-range measurement limited by lens flare, flash LiDAR/camera fusion calibration, sensor-realistic diffraction-limited image simulation, ADAS camera evaluation in rain, celestial imagery synthesis and a measurement-calibrated mmWave radar digital twin.
aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、ほか 12 個: emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigma、aug_vignette、vignette、distortion_map、psf_to_mtf、sfr_from_edge、mtf50、veiling_glare_index43 本
Neural and physics-based rendering for sensor simulation: NeRF and 3D Gaussian Splatting reconstructions of driving scenes, blur-aware and event-aided reconstruction, lens, flare and rolling-shutter modelling inside renderers, LiDAR novel-view synthesis and reflectance, and weather synthesis (heavy rain) for camera data. Bridges real recordings and controllable, physically meaningful re-simulation.
使う op(テーマ → op の対応表から。ノートで型と例を確かめてから使う):
gs_from_world(メッシュの世界 → ガウス、table → table)、gs_render(ガウスの描画、table × matrix → table)、gs_update(ガウスの更新、table × table → table)、gs_read_file(3DGS の読み込み、入力なし → table)、humanoid_impostors(向き × 位相の事前描画(安い代替)、table → table)importance_risk_estimate(発生率を上げて走らせ、重みで本来の事故率に戻す(不偏)、any → table)、poisson_events(稀な事象を頻度つきで置く、any → signal)、poisson_events_xt(場所と時刻で変わる発生率 λ(x, t)、any → any)、bus_stop_rate(停車中のバスの前後で上がる飛び出しの率、any → any)koschmieder(視程と消散係数(Koschmieder)、any × any × scalar × any → any)、beta_from_mor(気象光学距離 → 消散係数、scalar → scalar)、fog_beta_from_profile(画像の明るさの縦断から霧の濃さ、any × any × scalar × scalar × scalar → table)、veiling_luminance(まぶしさの光幕輝度、any × any → any)、sight_stop_speed(見える距離で止まれる速さ、scalar × scalar × scalar → scalar)、env_params(天候の母数、入力なし → table)fmcw_range_profile(FMCW の距離、beatcube → signal)、range_doppler_map(距離・速度の地図、beatcube → image2d)、doppler_shift(ドップラーの閉形式、any → any)、doppler_track(サイレンの周波数の追跡、signal → table)、tdoa_bearing(到着時間差から方向、signal × signal → table)psnr(画素の差、image2d × image2d → scalar)、ssim(構造の類似、image2d × image2d → scalar)、ms_ssim(多段の構造類似、image2d × image2d → scalar)、ssim_map(どこが違うかの地図、image2d × image2d → image2d)、fsim(位相一致と勾配の知覚的類似(FSIM)、image2d × image2d → scalar)、gmsd(勾配の類似の偏差(GMSD)、image2d × image2d → scalar)、vifp(情報忠実度(VIFp)、image2d × image2d → scalar)、tid2013_evaluate(指標を人の評価(TID2013)と順位相関で採点、any × any → table)、world_camera(真値つきの対の描画、table × matrix × matrix → table)curvature_speed_plan(曲率から速度の計画、any → table)、pure_pursuit_curvature(pure pursuit、any → table)、stanley_steer(Stanley、any → table)、stop_line_plan(停止線までの計画、scalar × scalar → table)、long_simulate(縦の運動、scalar × scalar × any → table)、bicycle_model_step(自転車モデル、any → any)aug_rolling_shutter(ローリングシャッター(斜線の傾き = v·t_line)、image → image)、aug_motion_blur(モーションブラー(スペクトルの零点)、image → image)、xkor_motion_blur(第 2 実装のブラー、image → image)Weather translation for driving imagery: a physics-guided GAN for controllable heavy-rain synthesis and a world-model-based method for realistic, scene-faithful weather translation of driving videos.
koschmieder(視程と消散係数(Koschmieder)、any × any × scalar × any → any)、beta_from_mor(気象光学距離 → 消散係数、scalar → scalar)、fog_beta_from_profile(画像の明るさの縦断から霧の濃さ、any × any × scalar × scalar × scalar → table)、veiling_luminance(まぶしさの光幕輝度、any × any → any)、sight_stop_speed(見える距離で止まれる速さ、scalar × scalar × scalar → scalar)、env_params(天候の母数、入力なし → table)、ほか 9 個: psnr、ssim、ms_ssim、ssim_map、fsim、gmsd、vifp、tid2013_evaluate、world_cameraEvent- and blur-aware 3D reconstruction: event-enhanced dynamic radiance fields from blurry monocular video, event-aided semantic 3DGS for humans and scenes, event-based 3DGS for high-speed robot egomotion, animatable avatars from motion-blurred video, and consumer-camera depth estimation.
importance_risk_estimate(発生率を上げて走らせ、重みで本来の事故率に戻す(不偏)、any → table)、poisson_events(稀な事象を頻度つきで置く、any → signal)、poisson_events_xt(場所と時刻で変わる発生率 λ(x, t)、any → any)、bus_stop_rate(停車中のバスの前後で上がる飛び出しの率、any → any)、curvature_speed_plan(曲率から速度の計画、any → table)、pure_pursuit_curvature(pure pursuit、any → table)、ほか 7 個: stanley_steer、stop_line_plan、long_simulate、bicycle_model_step、aug_rolling_shutter、aug_motion_blur、xkor_motion_blurRadiance-field methods that model sensor physics: NeuRAD for driving (rolling shutter, LiDAR ray drop), neural lens modelling, time-of-flight radiance fields, deblurring NeRFs (static and dynamic), road-surface novel views under sparse acquisition, a spike-camera simulator, and an attack on online HD-map construction.
gs_from_world(メッシュの世界 → ガウス、table → table)、gs_render(ガウスの描画、table × matrix → table)、gs_update(ガウスの更新、table × table → table)、gs_read_file(3DGS の読み込み、入力なし → table)、humanoid_impostors(向き × 位相の事前描画(安い代替)、table → table)Rendering components for realistic sensors: BRDF representation and acquisition, physically based lens flare in production rendering, XSIM unified sensor simulation with rolling-shutter-aware Gaussian rendering, raw low-light 3DGS, multispectral splats, physically calibrated rainfall for Gaussian driving scenes and road-defect mapping.
gs_from_world(メッシュの世界 → ガウス、table → table)、gs_render(ガウスの描画、table × matrix → table)、gs_update(ガウスの更新、table × table → table)、gs_read_file(3DGS の読み込み、入力なし → table)、humanoid_impostors(向き × 位相の事前描画(安い代替)、table → table)Light-transport building blocks: a generalised ray formulation for wave-optics rendering, precomputed lens transport maps for real-time lens simulation, and emitter-centric ray-triangle filtering for real-time LiDAR simulation in dynamic scenes.
fmcw_range_profile(FMCW の距離、beatcube → signal)、range_doppler_map(距離・速度の地図、beatcube → image2d)、doppler_shift(ドップラーの閉形式、any → any)、doppler_track(サイレンの周波数の追跡、signal → table)、tdoa_bearing(到着時間差から方向、signal × signal → table)Gaussian-splatting and rendering methods dealing with imperfect sensors: event- and spike-assisted deblur reconstruction, pose-aware dynamic deblurring, 5D covariance tracing for defocus and motion blur, specular scene reconstruction, joint RGB and LiDAR-reflectance inverse rendering, panoramic Gaussian LiDAR synthesis, hybrid neural/physics rendering, low-light 4D reconstruction and point-cloud completion under simulated fog.
gs_from_world(メッシュの世界 → ガウス、table → table)、gs_render(ガウスの描画、table × matrix → table)、gs_update(ガウスの更新、table × table → table)、gs_read_file(3DGS の読み込み、入力なし → table)、humanoid_impostors(向き × 位相の事前描画(安い代替)、table → table)119 本
LiDAR (and to a lesser degree radar and camera) perception under adverse weather and the simulators used to test it: physics-based fog, rain, snow and road-spray models applied to point clouds, climate-chamber and on-road degradation measurements, learned and ray-traced LiDAR simulators including intensity and ray drop, weather augmentation for robust 3D detection, and synthetic multimodal data generation.
使う op(テーマ → op の対応表から。ノートで型と例を確かめてから使う):
koschmieder(視程と消散係数(Koschmieder)、any × any × scalar × any → any)、beta_from_mor(気象光学距離 → 消散係数、scalar → scalar)、fog_beta_from_profile(画像の明るさの縦断から霧の濃さ、any × any × scalar × scalar × scalar → table)、veiling_luminance(まぶしさの光幕輝度、any × any → any)、sight_stop_speed(見える距離で止まれる速さ、scalar × scalar × scalar → scalar)、env_params(天候の母数、入力なし → table)lidar_spec(走査の仕様、入力なし → table)、lidar_scan(世界を走査、mesh × table × matrix → table)、ray_plane_range(平面までの距離(閉形式)、points × points → signal)、ray_box_ranges(箱までの距離(閉形式)、points × points → signal)、project_spherical(球面投影、points → image2d)、tof_multipath_phase(凹みの多重反射で ToF の位相がずれる量(閉形式)、入力なし → table)、tof_transport_depth(輸送行列で多重反射を入れた ToF の深度、table → table)world_build(コースから 3-D の世界、table → table)、world_camera(色・ラベル・深度・面番号を一度に、table × matrix × matrix → table)、world_move(物体を動かす、table → any)、env_render(太陽・霧・雨・夜、table × matrix × matrix → table)、tile_stream(終わらない地図、table × table → table)、gs_from_world(世界 → 3DGS、table → table)、carla_scene_world(CARLA の場面を自前の世界に(同じ場面を両方で)、table → table)、carla_depth_decode(CARLA の深度画像(RGB 符号)を m に、rgb → image2d)、carla_transform_matrix(CARLA の座標系(左手・度)↔ 自前の行列、any → matrix)、cr_read(CommonRoad のシナリオ XML を読む、any → table)、cr_drive(CommonRoad のシナリオを運転して採点、table → table)、osm_road_graph(OSM の道路網から地図、table → table)psnr(画素の差、image2d × image2d → scalar)、ssim(構造の類似、image2d × image2d → scalar)、ms_ssim(多段の構造類似、image2d × image2d → scalar)、ssim_map(どこが違うかの地図、image2d × image2d → image2d)、fsim(位相一致と勾配の知覚的類似(FSIM)、image2d × image2d → scalar)、gmsd(勾配の類似の偏差(GMSD)、image2d × image2d → scalar)、vifp(情報忠実度(VIFp)、image2d × image2d → scalar)、tid2013_evaluate(指標を人の評価(TID2013)と順位相関で採点、any × any → table)aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、emva_dynamic_range(ダイナミックレンジ、入力なし → table)、raw_demosaic_bilinear(デモザイク、image2d → rgb)、tone_map(階調、any × scalar → any)、estimate_noise(雑音の推定、image → feature)、noise_sigma(雑音の標準偏差、image2d → measurement)Two experimental studies on automotive LiDAR and point-cloud sensors in adverse weather: a simple benchmarking method for LiDAR performance in fog, and testing and validation of point-cloud sensors in rain, fog and related conditions.
koschmieder(視程と消散係数(Koschmieder)、any × any × scalar × any → any)、beta_from_mor(気象光学距離 → 消散係数、scalar → scalar)、fog_beta_from_profile(画像の明るさの縦断から霧の濃さ、any × any × scalar × scalar × scalar → table)、veiling_luminance(まぶしさの光幕輝度、any × any → any)、sight_stop_speed(見える距離で止まれる速さ、scalar × scalar × scalar → scalar)、env_params(天候の母数、入力なし → table)、ほか 7 個: lidar_spec、lidar_scan、ray_plane_range、ray_box_ranges、project_spherical、tof_multipath_phase、tof_transport_depthAdverse-weather perception and its simulation across sensors: physics-based LiDAR scattering augmentation (LISA), rain and fog performance models for LiDAR, multiple-scattering returns in fog, ground-effect (wet road) weather simulation, Monte Carlo FMCW LiDAR-radar fusion in fog, point-cloud augmentation and denoising, reviews of rain impact on cameras, radar simulation from LiDAR and camera, and robustness/distribution-shift studies.
koschmieder(視程と消散係数(Koschmieder)、any × any × scalar × any → any)、beta_from_mor(気象光学距離 → 消散係数、scalar → scalar)、fog_beta_from_profile(画像の明るさの縦断から霧の濃さ、any × any × scalar × scalar × scalar → table)、veiling_luminance(まぶしさの光幕輝度、any × any → any)、sight_stop_speed(見える距離で止まれる速さ、scalar × scalar × scalar → scalar)、env_params(天候の母数、入力なし → table)LiDAR under fog, rain and snow: physics-based fog simulation on real point clouds, LiDAR snowfall simulation, Monte Carlo signal-level rain/fog generation for ToF LiDAR, GAN-based fog synthesis, measured ToF LiDAR behaviour in a fog chamber, empirical on-road degradation, self-supervised desnowing, fog-aware fusion and localisation, GPU-rasterised LiDAR simulation, and a GAN for raw FMCW radar data.
koschmieder(視程と消散係数(Koschmieder)、any × any × scalar × any → any)、beta_from_mor(気象光学距離 → 消散係数、scalar → scalar)、fog_beta_from_profile(画像の明るさの縦断から霧の濃さ、any × any × scalar × scalar × scalar → table)、veiling_luminance(まぶしさの光幕輝度、any × any → any)、sight_stop_speed(見える距離で止まれる速さ、scalar × scalar × scalar → scalar)、env_params(天候の母数、入力なし → table)、ほか 7 個: lidar_spec、lidar_scan、ray_plane_range、ray_box_ranges、project_spherical、tof_multipath_phase、tof_transport_depthMaking simulated LiDAR realistic: learning ray drop and intensity from real data, physics-informed intensity modalities, GAN-based intensity rendering, NeRF-based LiDAR, adaptive splatting of point clouds for high-fidelity simulation, data-driven vegetation models, point-cloud generators from real scans, procedural PBR scenes and lightweight ML pipelines.
lidar_spec(走査の仕様、入力なし → table)、lidar_scan(世界を走査、mesh × table × matrix → table)、ray_plane_range(平面までの距離(閉形式)、points × points → signal)、ray_box_ranges(箱までの距離(閉形式)、points × points → signal)、project_spherical(球面投影、points → image2d)、tof_multipath_phase(凹みの多重反射で ToF の位相がずれる量(閉形式)、入力なし → table)、ほか 10 個: tof_transport_depth、psnr、ssim、ms_ssim、ssim_map、fsim、gmsd、vifp、tid2013_evaluate、world_cameraLiDAR and radar sensor simulation tools and their validation: HELIOS++ at HPC scale, OptiX-based LiMOX, physically accurate LiDAR for automotive digital twins, material-based LiDAR modelling, measured environmental influences on automotive LiDAR, road-spray models, snow filtering, VANE physics models, CPU real-time railway LiDAR, generation and validation of virtual point clouds, data-driven camera/LiDAR model reviews, object-level data-driven simulation and generative LiDAR worlds.
world_build(コースから 3-D の世界、table → table)、world_camera(色・ラベル・深度・面番号を一度に、table × matrix × matrix → table)、world_move(物体を動かす、table → any)、lidar_scan(同じ世界の LiDAR、mesh × table × matrix → table)、env_render(太陽・霧・雨・夜、table × matrix × matrix → table)、tile_stream(終わらない地図、table × table → table)、ほか 13 個: gs_from_world、carla_scene_world、carla_depth_decode、carla_transform_matrix、cr_read、cr_drive、osm_road_graph、lidar_spec、ray_plane_range、ray_box_ranges、project_spherical、tof_multipath_phase、tof_transport_depthMixed perception topics: automotive camera noise factors and their effect on object detection, sensor-model-based existence-probability fusion for track-to-track fusion, radar-based VRU tracking with metric learning, vehicle surface contamination and aerodynamic drag, a collision-free navigation survey and a simple Arduino safety system.
aug_shot_noise(光子の雑音、image → image)、aug_read_noise(読み出し雑音、image → image)、emva_snr_curve(EMVA 1288 の SNR 曲線、signal → matrix)、emva_photon_transfer(光子伝達曲線(PTC)から利得と読み出し雑音、signal × signal → table)、emva_dark_current(暗電流(露光時間の傾き)、signal × signal → table)、emva_spatial_nonuniformity(DSNU / PRNU(固定パターン雑音)、volume × volume → table)、ほか 5 個: emva_dynamic_range、raw_demosaic_bilinear、tone_map、estimate_noise、noise_sigmaPhysics-based synthetic data across modalities beyond driving: multimodal defence datasets, space-launch vehicle monitoring, synthetic data for laser-weld inspection, sim-real transfer frameworks for industrial object perception, vision-language detection of hard driving cases and multimodal road maintenance data.
Segmentation and augmentation with LiDAR intensity and synthetic data: reflectivity-aware LiDAR segmentation, physics-aware networks for LiDAR intensity simulation, instant domain augmentation across LiDAR sensors, road-marking wear from LiDAR intensity plus image segmentation, raindrop segmentation on windshields and a synthetic pedestrian dataset.
lidar_spec(走査の仕様、入力なし → table)、lidar_scan(世界を走査、mesh × table × matrix → table)、ray_plane_range(平面までの距離(閉形式)、points × points → signal)、ray_box_ranges(箱までの距離(閉形式)、points × points → signal)、project_spherical(球面投影、points → image2d)、tof_multipath_phase(凹みの多重反射で ToF の位相がずれる量(閉形式)、入力なし → table)、ほか 1 個: tof_transport_depthこの文献層で「使う op」に挙がった op と、それが出たクラスタ(上位 › 葉)。op から「どの知識の文脈で使うか」を引く。
| op | 出たクラスタ |
|---|---|
aliased_frequency |
image / images / hdr; camera / image / imaging |
aug_motion_blur |
image / images / hdr; shutter / rolling / camera; reconstruction / rendering / gaussian |
aug_read_noise |
image / images / hdr; shutter / rolling / camera; camera / image / imaging; lidar / weather / autonomous |
aug_rolling_shutter |
image / images / hdr; shutter / rolling / camera; reconstruction / rendering / gaussian |
aug_shot_noise |
image / images / hdr; shutter / rolling / camera; camera / image / imaging; lidar / weather / autonomous |
aug_vignette |
image / images / hdr; shutter / rolling / camera; camera / image / imaging |
beta_from_mor |
lidar / snowfall / surface; reconstruction / rendering / gaussian; lidar / weather / autonomous |
bicycle_model_step |
radar / automated / simulation; shutter / rolling / camera; reconstruction / rendering / gaussian |
bus_stop_rate |
reconstruction / rendering / gaussian |
carla_depth_decode |
lidar / snowfall / surface; radar / automated / simulation; lidar / weather / autonomous |
carla_scene_world |
lidar / snowfall / surface; radar / automated / simulation; lidar / weather / autonomous |
carla_transform_matrix |
lidar / snowfall / surface; radar / automated / simulation; lidar / weather / autonomous |
cr_drive |
lidar / snowfall / surface; radar / automated / simulation; lidar / weather / autonomous |
cr_read |
lidar / snowfall / surface; radar / automated / simulation; lidar / weather / autonomous |
curvature_speed_plan |
radar / automated / simulation; shutter / rolling / camera; reconstruction / rendering / gaussian |
deflicker |
image / images / hdr; camera / image / imaging |
dilemma_zone |
radar / automated / simulation |
distortion_map |
image / images / hdr; shutter / rolling / camera; camera / image / imaging |
doppler_shift |
radar / automated / simulation; reconstruction / rendering / gaussian |
doppler_track |
radar / automated / simulation; reconstruction / rendering / gaussian |
driver_style |
radar / automated / simulation |
emva_dark_current |
image / images / hdr; shutter / rolling / camera; camera / image / imaging; lidar / weather / autonomous |
emva_dynamic_range |
image / images / hdr; shutter / rolling / camera; camera / image / imaging; lidar / weather / autonomous |
emva_photon_transfer |
image / images / hdr; shutter / rolling / camera; camera / image / imaging; lidar / weather / autonomous |
emva_snr_curve |
image / images / hdr; shutter / rolling / camera; camera / image / imaging; lidar / weather / autonomous |
emva_spatial_nonuniformity |
image / images / hdr; shutter / rolling / camera; camera / image / imaging; lidar / weather / autonomous |
env_params |
lidar / snowfall / surface; reconstruction / rendering / gaussian; lidar / weather / autonomous |
env_render |
lidar / snowfall / surface; radar / automated / simulation; lidar / weather / autonomous |
estimate_noise |
image / images / hdr; shutter / rolling / camera; camera / image / imaging; lidar / weather / autonomous |
flash_frequency |
image / images / hdr; camera / image / imaging |
fmcw_range_profile |
radar / automated / simulation; reconstruction / rendering / gaussian |
fog_beta_from_profile |
lidar / snowfall / surface; reconstruction / rendering / gaussian; lidar / weather / autonomous |
fsim |
reconstruction / rendering / gaussian; lidar / weather / autonomous |
gmsd |
reconstruction / rendering / gaussian; lidar / weather / autonomous |
gs_from_world |
lidar / snowfall / surface; image / images / hdr; radar / automated / simulation; reconstruction / rendering / gaussian; lidar / weather / autonomous |
gs_read_file |
image / images / hdr; reconstruction / rendering / gaussian |
gs_render |
image / images / hdr; reconstruction / rendering / gaussian |
gs_update |
image / images / hdr; reconstruction / rendering / gaussian |
humanoid_impostors |
image / images / hdr; reconstruction / rendering / gaussian |
idm_equilibrium_gap |
radar / automated / simulation |
idm_platoon_simulate |
radar / automated / simulation |
importance_risk_estimate |
reconstruction / rendering / gaussian |
koschmieder |
lidar / snowfall / surface; reconstruction / rendering / gaussian; lidar / weather / autonomous |
lane_change_permitted |
radar / automated / simulation |
lateral_wobble |
radar / automated / simulation |
lidar_scan |
lidar / snowfall / surface; radar / automated / simulation; lidar / weather / autonomous |
lidar_spec |
lidar / snowfall / surface; lidar / weather / autonomous |
long_simulate |
radar / automated / simulation; shutter / rolling / camera; reconstruction / rendering / gaussian |
ms_ssim |
reconstruction / rendering / gaussian; lidar / weather / autonomous |
mtf50 |
image / images / hdr; shutter / rolling / camera; camera / image / imaging |
noise_sigma |
image / images / hdr; shutter / rolling / camera; camera / image / imaging; lidar / weather / autonomous |
occlusion_safe_speed |
radar / automated / simulation |
osm_road_graph |
lidar / snowfall / surface; radar / automated / simulation; lidar / weather / autonomous |
passing_decision |
radar / automated / simulation |
poisson_events |
reconstruction / rendering / gaussian |
poisson_events_xt |
reconstruction / rendering / gaussian |
project_spherical |
lidar / snowfall / surface; lidar / weather / autonomous |
psf_to_mtf |
image / images / hdr; shutter / rolling / camera; camera / image / imaging |
psnr |
reconstruction / rendering / gaussian; lidar / weather / autonomous |
pure_pursuit_curvature |
radar / automated / simulation; shutter / rolling / camera; reconstruction / rendering / gaussian |
range_doppler_map |
radar / automated / simulation; reconstruction / rendering / gaussian |
raw_demosaic_bilinear |
image / images / hdr; shutter / rolling / camera; camera / image / imaging; lidar / weather / autonomous |
ray_box_ranges |
lidar / snowfall / surface; lidar / weather / autonomous |
ray_plane_range |
lidar / snowfall / surface; lidar / weather / autonomous |
rss_lateral_check |
radar / automated / simulation |
rss_longitudinal_check |
radar / automated / simulation |
sfr_from_edge |
image / images / hdr; shutter / rolling / camera; camera / image / imaging |
sight_stop_speed |
lidar / snowfall / surface; reconstruction / rendering / gaussian; lidar / weather / autonomous |
skill_test_score |
radar / automated / simulation |
social_force_step |
radar / automated / simulation |
ssim |
reconstruction / rendering / gaussian; lidar / weather / autonomous |
ssim_map |
reconstruction / rendering / gaussian; lidar / weather / autonomous |
stanley_steer |
radar / automated / simulation; shutter / rolling / camera; reconstruction / rendering / gaussian |
stop_line_plan |
radar / automated / simulation; shutter / rolling / camera; reconstruction / rendering / gaussian |
tdoa_bearing |
radar / automated / simulation; reconstruction / rendering / gaussian |
tid2013_evaluate |
reconstruction / rendering / gaussian; lidar / weather / autonomous |
tile_stream |
lidar / snowfall / surface; radar / automated / simulation; lidar / weather / autonomous |
tof_multipath_phase |
lidar / snowfall / surface; lidar / weather / autonomous |
tof_transport_depth |
lidar / snowfall / surface; lidar / weather / autonomous |
tone_map |
image / images / hdr; shutter / rolling / camera; camera / image / imaging; lidar / weather / autonomous |
ttc_from_range |
radar / automated / simulation |
ttc_truth |
radar / automated / simulation |
turn_maneuver_check |
radar / automated / simulation |
veiling_glare_index |
image / images / hdr; shutter / rolling / camera; camera / image / imaging |
veiling_luminance |
lidar / snowfall / surface; reconstruction / rendering / gaussian; lidar / weather / autonomous |
vifp |
reconstruction / rendering / gaussian; lidar / weather / autonomous |
vignette |
image / images / hdr; shutter / rolling / camera; camera / image / imaging |
world_build |
lidar / snowfall / surface; radar / automated / simulation; lidar / weather / autonomous |
world_camera |
lidar / snowfall / surface; radar / automated / simulation; reconstruction / rendering / gaussian; lidar / weather / autonomous |
world_move |
lidar / snowfall / surface; radar / automated / simulation; lidar / weather / autonomous |
xkor_motion_blur |
image / images / hdr; shutter / rolling / camera; reconstruction / rendering / gaussian |