8 papers
DDStereo: Efficient Dual Decoder Transformers for Stereo 3D Road Anomaly Detection
Shiyi Mu, Zichong Gu, Zhiqi Ai +2
Stereo-based 3D obstacle perception for autonomous driving is currently constrained by an imbalanced triplet: deployment cost, detection accuracy, and open-set adaptability. While…
ETA-VLA: Efficient Token Adaptation via Temporal Fusion and Intra-LLM Sparsification for Vision-Language-Action Models
Yiru Wang, Anqing Jiang, Shuo Wang +3
The integration of Vision-Language-Action (VLA) models into autonomous driving systems offers a unified framework for interpreting complex scenes and executing control commands. Ho…
HiST-VLA: A Hierarchical Spatio-Temporal Vision-Language-Action Model for End-to-End Autonomous Driving
Yiru Wang, Zichong Gu, Yu Gao +5
Vision-Language-Action (VLA) models offer promising capabilities for autonomous driving through multimodal understanding. However, their utilization in safety-critical scenarios is…
StereoDETR: Stereo-based Transformer for 3D Object Detection
Shiyi Mu, Zichong Gu, Zhiqi Ai +3
Compared to monocular 3D object detection, stereo-based 3D methods offer significantly higher accuracy but still suffer from high computational overhead and latency. The state-of-t…
AnchDrive: Bootstrapping Diffusion Policies with Hybrid Trajectory Anchors for End-to-End Driving
Jinhao Chai, Anqing Jiang, Hao Jiang +4
End-to-end multi-modal planning has become a transformative paradigm in autonomous driving, effectively addressing behavioral multi-modality and the generalization challenge in lon…
Stereo-based 3D Anomaly Object Detection for Autonomous Driving: A New Dataset and Baseline
Shiyi Mu, Zichong Gu, Hanqi Lyu +2
3D detection technology is widely used in the field of autonomous driving, with its application scenarios gradually expanding from enclosed highways to open conventional roads. For…