56 citations · 230 across the 24 of their papers we have counts for
24 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…
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…
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…
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…
SEGA: Semantic Guided Attention on Visual Prototype for Few-Shot Learning
Fengyuan Yang, Ruiping Wang, Xilin Chen
Teaching machines to recognize a new category based on few training samples especially only one remains challenging owing to the incomprehensive understanding of the novel category…
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…
Sketching Image Gist: Human-Mimetic Hierarchical Scene Graph Generation
Wenbin Wang, Ruiping Wang, Shiguang Shan +1
Scene graph aims to faithfully reveal humans' perception of image content. When humans analyze a scene, they usually prefer to describe image gist first, namely major objects and k…
Multi-Modal Graph Neural Network for Joint Reasoning on Vision and Scene Text
Difei Gao, Ke Li, Ruiping Wang +2
Answering questions that require reading texts in an image is challenging for current models. One key difficulty of this task is that rare, polysemous, and ambiguous words frequent…
Deep Heterogeneous Hashing for Face Video Retrieval
Shishi Qiao, Ruiping Wang, Shiguang Shan +1
Retrieving videos of a particular person with face image as a query via hashing technique has many important applications. While face images are typically represented as vectors in…
Cross-modal Scene Graph Matching for Relationship-aware Image-Text Retrieval
Sijin Wang, Ruiping Wang, Ziwei Yao +2
Image-text retrieval of natural scenes has been a popular research topic. Since image and text are heterogeneous cross-modal data, one of the key challenges is how to learn compreh…
Transferable Contrastive Network for Generalized Zero-Shot Learning
Huajie Jiang, Ruiping Wang, Shiguang Shan +1
Zero-shot learning (ZSL) is a challenging problem that aims to recognize the target categories without seen data, where semantic information is leveraged to transfer knowledge from…
CRIC: A VQA Dataset for Compositional Reasoning on Vision and Commonsense
Difei Gao, Ruiping Wang, Shiguang Shan +1
Alternatively inferring on the visual facts and commonsense is fundamental for an advanced VQA system. This ability requires models to go beyond the literal understanding of common…
WIDER Face and Pedestrian Challenge 2018: Methods and Results
Chen Change Loy, Dahua Lin, Wanli Ouyang +49
This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian. The challenge focuses on the problem of precise localization of human faces and bodies, and accurat…
Learning Class Prototypes via Structure Alignment for Zero-Shot Recognition
Huajie Jiang, Ruiping Wang, Shiguang Shan +1
Zero-shot learning (ZSL) aims to recognize objects of novel classes without any training samples of specific classes, which is achieved by exploiting the semantic information and a…
Structure Inference Net: Object Detection Using Scene-Level Context and Instance-Level Relationships
Yong Liu, Ruiping Wang, Shiguang Shan +1
Context is important for accurate visual recognition. In this work we propose an object detection algorithm that not only considers object visual appearance, but also makes use of…
Geometry-aware Similarity Learning on SPD Manifolds for Visual Recognition
Zhiwu Huang, Ruiping Wang, Xianqiu Li +4
Symmetric Positive Definite (SPD) matrices have been widely used for data representation in many visual recognition tasks. The success mainly attributes to learning discriminative…
Cross Euclidean-to-Riemannian Metric Learning with Application to Face Recognition from Video
Zhiwu Huang, Ruiping Wang, Shiguang Shan +2
Riemannian manifolds have been widely employed for video representations in visual classification tasks including video-based face recognition. The success mainly derives from lear…
Dual Purpose Hashing
Haomiao Liu, Ruiping Wang, Shiguang Shan +1
Recent years have seen more and more demand for a unified framework to address multiple realistic image retrieval tasks concerning both category and attributes. Considering the sca…
Learning Expressionlets via Universal Manifold Model for Dynamic Facial Expression Recognition
Mengyi Liu, Shiguang Shan, Ruiping Wang +1
Facial expression is temporally dynamic event which can be decomposed into a set of muscle motions occurring in different facial regions over various time intervals. For dynamic ex…
Learning Mid-level Words on Riemannian Manifold for Action Recognition
Mengyi Liu, Ruiping Wang, Shiguang Shan +1
Human action recognition remains a challenging task due to the various sources of video data and large intra-class variations. It thus becomes one of the key issues in recent resea…