1 citations · 1 across the 3 of their papers we have counts for
7 papers
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…
PreSem-Surf: RGB-D Surface Reconstruction with Progressive Semantic Modeling and SG-MLP Pre-Rendering Mechanism
Yuyan Ye, Hang Xu, Yanghang Huang +2
This paper proposes PreSem-Surf, an optimized method based on the Neural Radiance Field (NeRF) framework, capable of reconstructing high-quality scene surfaces from RGB-D sequences…
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…
Aligning Multimodal LLM with Human Preference: A Survey
Tao Yu, Yi-Fan Zhang, Chaoyou Fu +14
Large language models (LLMs) can handle a wide variety of general tasks with simple prompts, without the need for task-specific training. Multimodal Large Language Models (MLLMs),…
VicKAM: Visual Conceptual Knowledge Guided Action Map for Weakly Supervised Group Activity Recognition
Zhuming Wang, Yihao Zheng, Jiarui Li +5
Existing weakly supervised group activity recognition methods rely on object detectors or attention mechanisms to capture key areas automatically. However, they overlook the semant…