[CVPR 2023 Best Paper Award] Planning-oriented Autonomous Driving
- autonomous-driving
- end-to-end-autonomous-driving
- motion-prediction
- multi-object-tracking
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[CVPR 2023 Best Paper Award] Planning-oriented Autonomous Driving
pySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.
Modular autonomous driving platform running on the CARLA simulator and real-world vehicles.
Independent reproduction of SuperMimic (arXiv:2610.28480) on mjlab/MuJoCo Warp, written from the paper before the official release. For the authors' code see HybridRobotics/supermimic. Kept as a record: experiment log, full BONES-SEED results, checkpoint.
HALO: Perceptive Humanoid Motion from Simulation
CARLA-based cooperative perception system integrating YOLO26n, V2I communication, sensor fusion, TTC risk assessment, and automated braking.