4 citations · 5 across the 13 of their papers we have counts for
6 papers · 1 filter
DreamTraj: Generating 6-DoF Object Trajectories by Reading Unrendered Video Diffusion Latents
Tongsheng Ding, Zhen Luo, Yixuan Yang +4
Accurate prediction of object trajectories during manipulation is essential for closing the perception-action loop. Progress is limited on two fronts: available datasets lack fine-…
DeSeG: Decoupling Semantic Intent and Geometric Constraints for Physically Plausible Human-Scene Interaction
Jiakun Li, Zhe Li, Wenqiang Wu +4
Synthesizing physically plausible human-scene interactions (HSI) remains a critical challenge in computer vision and the development of human avatars. Although recent generative mo…
GVC-Seg: Training-Free 3D Instance Segmentation via Geometric Visual Correspondence
Liang Xu, Fangjing Wang, Jinyu Yang +1
Accurate 3D instance segmentation in point cloud data is critical for machine vision applications. Recent advancements leverage multiple pre-trained foundation models to generate 3…
LiveVLN: Breaking the Stop-and-Go Loop in Vision-Language Navigation
Xiangchen Wang, Weiye Zhu, Teng Wang +5
Recent navigation systems achieve strong benchmark results, yet real-world deployment often remains visibly stop-and-go. This bottleneck arises because the sense-inference-executio…
Show Me When and Where: Towards Referring Video Object Segmentation in the Wild
Mingqi Gao, Jinyu Yang, Jingnan Luo +4
Referring video object segmentation (RVOS) has recently generated great popularity in computer vision due to its widespread applications. Existing RVOS setting contains elaborately…
RADAR: Closed-Loop Robotic Data Generation via Semantic Planning and Autonomous Causal Environment Reset
Yongzhong Wang, Keyu Zhu, Yong Zhong +3
The acquisition of large-scale physical interaction data, a critical prerequisite for modern robot learning, is severely bottlenecked by the prohibitive cost and scalability limits…