1 citations · 2 across the 19 of their papers we have counts for
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X-Drive: Cross-modality consistent multi-sensor data synthesis for driving scenarios
Yichen Xie, Chenfeng Xu, Chensheng Peng +6
Recent advancements have exploited diffusion models for the synthesis of either LiDAR point clouds or camera image data in driving scenarios. Despite their success in modeling sing…
DeSiRe-GS: 4D Street Gaussians for Static-Dynamic Decomposition and Surface Reconstruction for Urban Driving Scenes
Chensheng Peng, Chengwei Zhang, Yixiao Wang +6
We present DeSiRe-GS, a self-supervised gaussian splatting representation, enabling effective static-dynamic decomposition and high-fidelity surface reconstruction in complex drivi…
DexH2R: Task-oriented Dexterous Manipulation from Human to Robots
Shuqi Zhao, Xinghao Zhu, Yuxin Chen +5
Dexterous manipulation is a critical aspect of human capability, enabling interaction with a wide variety of objects. Recent advancements in learning from human demonstrations and…
TrajSSL: Trajectory-Enhanced Semi-Supervised 3D Object Detection
Philip Jacobson, Yichen Xie, Mingyu Ding +4
Semi-supervised 3D object detection is a common strategy employed to circumvent the challenge of manually labeling large-scale autonomous driving perception datasets. Pseudo-labeli…
Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation
Yixiao Wang, Chen Tang, Lingfeng Sun +8
Diffusion models are promising for joint trajectory prediction and controllable generation in autonomous driving, but they face challenges of inefficient inference steps and high c…
Sparse Diffusion Policy: A Sparse, Reusable, and Flexible Policy for Robot Learning
Yixiao Wang, Yifei Zhang, Mingxiao Huo +8
The increasing complexity of tasks in robotics demands efficient strategies for multitask and continual learning. Traditional models typically rely on a universal policy for all ta…
RoadBEV: Road Surface Reconstruction in Bird's Eye View
Tong Zhao, Lei Yang, Yichen Xie +3
Road surface conditions, especially geometry profiles, enormously affect driving performance of autonomous vehicles. Vision-based online road reconstruction promisingly captures ro…
Cohere3D: Exploiting Temporal Coherence for Unsupervised Representation Learning of Vision-based Autonomous Driving
Yichen Xie, Hongge Chen, Gregory P. Meyer +6
Due to the lack of depth cues in images, multi-frame inputs are important for the success of vision-based perception, prediction, and planning in autonomous driving. Observations f…