4 citations · 6 across the 13 of their papers we have counts for
14 papers
GEAR: GEometry-motion Alternating Refinement for Articulated Object Modeling with Gaussian Splatting
Jialin Li, Bin Fu, Ruiping Wang +1
High-fidelity interactive digital assets are essential for embodied intelligence and robotic interaction, yet articulated objects remain challenging to reconstruct due to their com…
From Semantics to Pixels: Coarse-to-Fine Masked Autoencoders for Hierarchical Visual Understanding
Wenzhao Xiang, Yue Wu, Hongyang Yu +3
Self-supervised visual pre-training methods face an inherent tension: contrastive learning (CL) captures global semantics but loses fine-grained detail, while masked image modeling…
RoboPCA: Pose-centered Affordance Learning from Human Demonstrations for Robot Manipulation
Zhanqi Xiao, Ruiping Wang, Xilin Chen
Understanding spatial affordances -- comprising the contact regions of object interaction and the corresponding contact poses -- is essential for robots to effectively manipulate o…
Uni-Skill: Building Self-Evolving Skill Repository for Generalizable Robotic Manipulation
Senwei Xie, Yuntian Zhang, Ruiping Wang +1
While skill-centric approaches leverage foundation models to enhance generalization in compositional tasks, they often rely on fixed skill libraries, limiting adaptability to new t…
VisKnow: Constructing Visual Knowledge Base for Object Understanding
Ziwei Yao, Qiyang Wan, Ruiping Wang +1
Understanding objects is fundamental to computer vision. Beyond object recognition that provides only a category label as typical output, in-depth object understanding represents a…
A Survey on Interpretability in Visual Recognition
Qiyang Wan, Chengzhi Gao, Ruiping Wang +1
Visual recognition models have achieved unprecedented success in various tasks. While researchers aim to understand the underlying mechanisms of these models, the growing demand fo…
MoTE: Mixture of Ternary Experts for Memory-efficient Large Multimodal Models
Hongyu Wang, Jiayu Xu, Ruiping Wang +5
Large multimodal Mixture-of-Experts (MoEs) effectively scale the model size to boost performance while maintaining fixed active parameters. However, previous works primarily utiliz…
BitVLA: 1-bit Vision-Language-Action Models for Robotics Manipulation
Hongyu Wang, Chuyan Xiong, Ruiping Wang +1
Deploying powerful Vision-Language-Action (VLA) models on edge devices is limited by their massive size. In this paper, we take a deployment-oriented view of VLA training: we targe…
GS-LTS: 3D Gaussian Splatting-Based Adaptive Modeling for Long-Term Service Robots
Bin Fu, Jialin Li, Bin Zhang +2
3D Gaussian Splatting (3DGS) has garnered significant attention in robotics for its explicit, high fidelity dense scene representation, demonstrating strong potential for robotic a…
Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation
Senwei Xie, Hongyu Wang, Zhanqi Xiao +2
Zero-shot generalization across various robots, tasks and environments remains a significant challenge in robotic manipulation. Policy code generation methods use executable code t…
Blocks as Probes: Dissecting Categorization Ability of Large Multimodal Models
Bin Fu, Qiyang Wan, Jialin Li +2
Categorization, a core cognitive ability in humans that organizes objects based on common features, is essential to cognitive science as well as computer vision. To evaluate the ca…
M4U: Evaluating Multilingual Understanding and Reasoning for Large Multimodal Models
Hongyu Wang, Jiayu Xu, Senwei Xie +6
Multilingual capability is an essential aspect for large multimodal models, since they are usually deployed across various countries and languages. However, most existing benchmark…
Glance and Focus: Memory Prompting for Multi-Event Video Question Answering
Ziyi Bai, Ruiping Wang, Xilin Chen
Video Question Answering (VideoQA) has emerged as a vital tool to evaluate agents' ability to understand human daily behaviors. Despite the recent success of large vision language…
Topic Scene Graph Generation by Attention Distillation from Caption
W. Wang, R. Wang, X. Chen
If an image tells a story, the image caption is the briefest narrator. Generally, a scene graph prefers to be an omniscient generalist, while the image caption is more willing to b…