https://github.com/fudan-zvg/wovogen
공식 코드WoVoGen: World Volume-aware Diffusion for Controllable Multi-camera Driving Scene Generation
Papers with Code 아카이브
Autonomous Driving
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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Autonomous driving is the task of driving a vehicle without human conduction.
Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.
<span style="color:grey; opacity: 0.5">(Image credit: Exploring the Limitations of Behavior Cloning for Autonomous Driving)</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/fuhaha824/pg-attack
공식 코드https://github.com/fujiawei0724/interactionnet
공식 코드InteractionNet: Joint Planning and Prediction for Autonomous Driving with Transformers
https://github.com/fwesterhout/Smooth-Trajectron
공식 코드Smooth-Trajectron++: Augmenting the Trajectron++ behaviour prediction model with smooth attention
https://github.com/fzhiheng/RoGS
공식 코드RoGs: Large Scale Road Surface Reconstruction with Meshgrid Gaussian
https://github.com/fzi-forschungszentrum-informatik/anovox
공식 코드AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving
https://github.com/fzi-forschungszentrum-informatik/informed_rl
공식 코드Informed Reinforcement Learning for Situation-Aware Traffic Rule Exceptions
https://github.com/fzi-forschungszentrum-informatik/muvo
공식 코드MUVO: A Multimodal World Model with Spatial Representations for Autonomous Driving
https://github.com/fzi-forschungszentrum-informatik/quantification_road_user_behavior/blob/main/README.md
공식 코드Quantification of Actual Road User Behavior on the Basis of Given Traffic Rules
https://github.com/gabriel-vanzandycke/deepsport
공식 코드Context-Aware 3D Object Localization from Single Calibrated Images: A Study of Basketballs
https://github.com/galaxy-zrx/edgehead
공식 코드https://github.com/gandolfczjh/3d2fool
공식 코드Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous Driving
https://github.com/ganglii/devsafety
공식 코드A Retention-Centric Framework for Continual Learning with Guaranteed Model Developmental Safety
https://github.com/ganwanshui/simpleoccupancy
공식 코드A Simple Framework for 3D Occupancy Estimation in Autonomous Driving
https://github.com/gaoyinfeng/piwm
공식 코드https://github.com/gaperezsa/3deformrs
공식 코드https://github.com/garfield-cpp/hgsfusion
공식 코드HGSFusion: Radar-Camera Fusion with Hybrid Generation and Synchronization for 3D Object Detection
https://github.com/garrickbrazil/M3D-RPN
공식 코드M3D-RPN: Monocular 3D Region Proposal Network for Object Detection
https://github.com/gaurav00700/selfsupervised-nvsf
공식 코드https://github.com/gaussianer/fasterseg
공식 코드https://github.com/ge25nab/Awesome-VLM-AD-ITS
공식 코드Vision Language Models in Autonomous Driving: A Survey and Outlook
https://github.com/geoai4cities/pgs-cam
공식 코드Towards Explainable LiDAR Point Cloud Semantic Segmentation via Gradient Based Target Localization
https://github.com/geoaigroup/geoai-ecrs2023
공식 코드https://github.com/georgeeskandar/towards-pragmatic-semantic-image-synthesis-for-urban-scenes
공식 코드https://github.com/georgeliu233/scene-rep-transformer
공식 코드https://github.com/georgeliu233/strajnet
공식 코드https://github.com/georghess/neurad-studio
공식 코드https://github.com/getterupper/PreWorld
공식 코드Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving
https://github.com/ghimiremukesh/autonomous-driving
공식 코드Lane Change Decision-Making through Deep Reinforcement Learning
https://github.com/ghostish/objectcentricocccompletion
공식 코드Towards Flexible 3D Perception: Object-Centric Occupancy Completion Augments 3D Object Detection
https://github.com/ghostish/open3dsot
공식 코드Beyond 3D Siamese Tracking: A Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds
https://github.com/giandbt/synboost
공식 코드https://github.com/giantseaweed/rocas
공식 코드ROCAS: Root Cause Analysis of Autonomous Driving Accidents via Cyber-Physical Co-mutation
https://github.com/gigaai-research/general-world-models-survey
공식 코드Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond
https://github.com/gist-ailab/mart
공식 코드MART: MultiscAle Relational Transformer Networks for Multi-agent Trajectory Prediction
https://github.com/git-disl/EVA
공식 코드Parallel Detection for Efficient Video Analytics at the Edge
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.