5 papers
BridgeV2W: Bridging Video Generation Models to Embodied World Models via Embodiment Masks
Yixiang Chen, Peiyan Li, Jiabing Yang +8
Embodied world models have emerged as a promising paradigm in robotics, most of which leverage large-scale Internet videos or pretrained video generation models to enrich visual an…
VERM: Leveraging Foundation Models to Create a Virtual Eye for Efficient 3D Robotic Manipulation
Yixiang Chen, Yan Huang, Keji He +2
When performing 3D manipulation tasks, robots have to execute action planning based on perceptions from multiple fixed cameras. The multi-camera setup introduces substantial redund…
IKOD: Mitigating Visual Attention Degradation in Large Vision-Language Models
Jiabing Yang, Chenhang Cui, Yiyang Zhou +6
Recent advancements in Large Vision-Language Models (LVLMs) have demonstrated significant progress across multiple domains. However, these models still face the inherent challenge…
EC-Flow: Enabling Versatile Robotic Manipulation from Action-Unlabeled Videos via Embodiment-Centric Flow
Yixiang Chen, Peiyan Li, Yan Huang +3
Current language-guided robotic manipulation systems often require low-level action-labeled datasets for imitation learning. While object-centric flow prediction methods mitigate t…
BridgeVLA: Input-Output Alignment for Efficient 3D Manipulation Learning with Vision-Language Models
Peiyan Li, Yixiang Chen, Hongtao Wu +6
Recently, leveraging pre-trained vision-language models (VLMs) for building vision-language-action (VLA) models has emerged as a promising approach to effective robot manipulation…