25 citations · 27 across the 14 of their papers we have counts for
5 papers · 1 filter
Geometry-Guided Modeling of Foundation Features Enables Generalizable Object Shape Deformation Learning
Yiyao Ma, Kai Chen, Zhongxiang Zhou +5
Monocular 3D shape recovery is fundamental to geometric understanding, yet achieving robust generalization across arbitrary viewpoints and unseen object categories remains a signif…
CNSv2: Probabilistic Correspondence Encoded Neural Image Servo
Anzhe Chen, Hongxiang Yu, Shuxin Li +5
Visual servo based on traditional image matching methods often requires accurate keypoint correspondence for high precision control. However, keypoint detection or matching tends t…
Open-Set Object Detection Using Classification-free Object Proposal and Instance-level Contrastive Learning
Zhongxiang Zhou, Yifei Yang, Yue Wang +1
Detecting both known and unknown objects is a fundamental skill for robot manipulation in unstructured environments. Open-set object detection (OSOD) is a promising direction to ha…
Learn to Differ: Sim2Real Small Defection Segmentation Network
Zexi Chen, Zheyuan Huang, Yunkai Wang +3
Recent studies on deep-learning-based small defection segmentation approaches are trained in specific settings and tend to be limited by fixed context. Throughout the training, the…
REDE: End-to-end Object 6D Pose Robust Estimation Using Differentiable Outliers Elimination
Weitong Hua, Zhongxiang Zhou, Jun Wu +3
Object 6D pose estimation is a fundamental task in many applications. Conventional methods solve the task by detecting and matching the keypoints, then estimating the pose. Recent…