https://github.com/wudongming97/topomlp
공식 코드TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoning
Papers with Code 아카이브
Autonomous Driving
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 6
- 평가표
- 4
- 보존된 평가 기록
- 23
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/wuhanstudio/adversarial-camera
공식 코드A Human-in-the-Middle Attack against Object Detection Systems
https://github.com/wuhanstudio/adversarial-driving
공식 코드Adversarial Driving: Attacking End-to-End Autonomous Driving
https://github.com/wuhanstudio/whitebox-adversarial-toolbox
공식 코드A Human-in-the-Middle Attack against Object Detection Systems
https://github.com/wujingda/prioritized-human-in-the-loop-end-to-end-autonomous-driving
공식 코드Prioritized Experience-based Reinforcement Learning with Human Guidance for Autonomous Driving
https://github.com/wutad-wjy/charms
공식 코드CHARMS: A Cognitive Hierarchical Agent for Reasoning and Motion Stylization in Autonomous Driving
https://github.com/wyddmw/WiseAD
공식 코드WiseAD: Knowledge Augmented End-to-End Autonomous Driving with Vision-Language Model
https://github.com/wzm5853/bench4merge
공식 코드https://github.com/wzzheng/doe
공식 코드Doe-1: Closed-Loop Autonomous Driving with Large World Model
https://github.com/wzzheng/gaussianad
공식 코드https://github.com/wzzheng/genad
공식 코드https://github.com/wzzheng/gpd
공식 코드https://github.com/wzzheng/hass
공식 코드Hardness-Aware Scene Synthesis for Semi-Supervised 3D Object Detection
https://github.com/wzzheng/occsora
공식 코드OccSora: 4D Occupancy Generation Models as World Simulators for Autonomous Driving
https://github.com/wzzheng/occworld
공식 코드OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving
https://github.com/wzzheng/pointocc
공식 코드PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction
https://github.com/wzzheng/stag
공식 코드Stag-1: Towards Realistic 4D Driving Simulation with Video Generation Model
https://github.com/wzzheng/tpvformer
공식 코드Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction
https://github.com/xaviergrool/fgfusion
공식 코드FGFusion: Fine-Grained Lidar-Camera Fusion for 3D Object Detection
https://github.com/xccyue/MutualDistance
공식 코드Scene-aware Human Motion Forecasting via Mutual Distance Prediction
https://github.com/xiandaguo/drive-mllm
공식 코드https://github.com/xiandaguo/openstereo
공식 코드OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline
https://github.com/xiangbogaobarry/mambast
공식 코드MambaST: A Plug-and-Play Cross-Spectral Spatial-Temporal Fuser for Efficient Pedestrian Detection
https://github.com/xiangchong1/3d-adv-pc
공식 코드https://github.com/xiangxu-0103/lima
공식 코드https://github.com/xiangxu-0103/superflow
공식 코드4D Contrastive Superflows are Dense 3D Representation Learners
https://github.com/xiaoaoran/3d_url_survey
공식 코드Unsupervised Point Cloud Representation Learning with Deep Neural Networks: A Survey
https://github.com/xiaoaoran/semanticstf
공식 코드3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds
https://github.com/xiaogangpeng/tbiformer
공식 코드Trajectory-Aware Body Interaction Transformer for Multi-Person Pose Forecasting
https://github.com/xiaohao-xu/unified-pretrain-ad
공식 코드https://github.com/xiaolongtang23/hpnet
공식 코드HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attention
https://github.com/xiaomi-mlab/mila.github.io
공식 코드MiLA: Multi-view Intensive-fidelity Long-term Video Generation World Model for Autonomous Driving
https://github.com/xiaomi/cgnet
공식 코드https://github.com/xiaomiaozhang/Co-MTP
공식 코드https://github.com/xieyuser/semi-sd
공식 코드Semi-SD: Semi-Supervised Metric Depth Estimation via Surrounding Cameras for Autonomous Driving
https://github.com/xincoder/GRIP
공식 코드GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous Driving
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.