78 citations · 81 across the 12 of their papers we have counts for
14 papers
RoPT: Robust 6DoF Object Pose Tracking in Video
Yongqing Liang, Yuzhong Chen, Sihang Li +7
Accurate 6-DoF object pose tracking is essential for robotic interaction, yet conventional monocular pipelines frequently suffer from catastrophic divergence under rapid object mot…
Vision-Force Admittance Learning for Peg Insertion into a Movable Hole
Yuzhong Chen, Yongqing Liang, Yunzhi Xu +6
Precise manipulation in dynamic environments, whether induced by a mobile robot base or a target with unknown motion, remains a major challenge in robotics. Manipulation in dynamic…
SCD4VPR: Multi-modal Scene Change Detection for Long-term Visual Place Recognition Database Update
Diwei Sheng, Vijayraj Gohil, Satyam Gaba +5
Long-term autonomy in mobile robotics requires maps that remain accurate as environments change over time. Visual Place Recognition (VPR), a core localization capability, degrades…
SolidGS: Consolidating Gaussian Surfel Splatting for Sparse-View Surface Reconstruction
Zhuowen Shen, Yuan Liu, Zhang Chen +9
Gaussian splatting has achieved impressive improvements for both novel-view synthesis and surface reconstruction from multi-view images. However, current methods still struggle to…
AURORA: Automated Unleash of 3D Room Outlines for VR Applications
Huijun Han, Yongqing Liang, Yuanlong Zhou +3
Creating realistic VR experiences is challenging due to the labor-intensive process of accurately replicating real-world details into virtual scenes, highlighting the need for auto…
CLAP: Concave Linear APproximation for Quadratic Graph Matching
Yongqing Liang, Huijun Han, Xin Li
Solving point-wise feature correspondence in visual data is a fundamental problem in computer vision. A powerful model that addresses this challenge is to formulate it as graph mat…
A Survey on Computational Solutions for Reconstructing Complete Objects by Reassembling Their Fractured Parts
Jiaxin Lu, Yongqing Liang, Huijun Han +4
Reconstructing a complete object from its parts is a fundamental problem in many scientific domains. The purpose of this article is to provide a systematic survey on this topic. Th…
Enhancing Weakly Supervised Semantic Segmentation with Multi-modal Foundation Models: An End-to-End Approach
Elham Ravanbakhsh, Cheng Niu, Yongqing Liang +2
Semantic segmentation is a core computer vision problem, but the high costs of data annotation have hindered its wide application. Weakly-Supervised Semantic Segmentation (WSSS) of…
Deep video representation learning: a survey
Elham Ravanbakhsh, Yongqing Liang, J. Ramanujam +1
This paper provides a review on representation learning for videos. We classify recent spatiotemporal feature learning methods for sequential visual data and compare their pros and…
Skull-to-Face: Anatomy-Guided 3D Facial Reconstruction and Editing
Yongqing Liang, Congyi Zhang, Junli Zhao +2
Deducing the 3D face from a skull is a challenging task in forensic science and archaeology. This paper proposes an end-to-end 3D face reconstruction pipeline and an exploration me…
Disentangled Clothed Avatar Generation from Text Descriptions
Jionghao Wang, Yuan Liu, Zhiyang Dou +7
In this paper, we introduce a novel text-to-avatar generation method that separately generates the human body and the clothes and allows high-quality animation on the generated ava…
Neural Parametric Surfaces for Shape Modeling
Lei Yang, Yongqing Liang, Xin Li +6
The recent surge of utilizing deep neural networks for geometric processing and shape modeling has opened up exciting avenues. However, there is a conspicuous lack of research effo…
Video Object Segmentation with Adaptive Feature Bank and Uncertain-Region Refinement
Yongqing Liang, Xin Li, Navid Jafari +1
We propose a new matching-based framework for semi-supervised video object segmentation (VOS). Recently, state-of-the-art VOS performance has been achieved by matching-based algori…
Salient Object Detection with Convex Hull Overlap
Yongqing Liang
Salient object detection plays an important part in a vision system to detect important regions. Convolutional neural network (CNN) based methods directly train their models with l…