18 citations · 56 across the 16 of their papers we have counts for
16 papers
ManiPose: A Comprehensive Benchmark for Pose-aware Object Manipulation in Robotics
Qiaojun Yu, Ce Hao, Junbo Wang +6
Robotic manipulation in everyday scenarios, especially in unstructured environments, requires skills in pose-aware object manipulation (POM), which adapts robots' grasping and hand…
RPMArt: Towards Robust Perception and Manipulation for Articulated Objects
Junbo Wang, Wenhai Liu, Qiaojun Yu +4
Articulated objects are commonly found in daily life. It is essential that robots can exhibit robust perception and manipulation skills for articulated objects in real-world roboti…
CRIN: Rotation-Invariant Point Cloud Analysis and Rotation Estimation via Centrifugal Reference Frame
Yujing Lou, Zelin Ye, Yang You +5
Various recent methods attempt to implement rotation-invariant 3D deep learning by replacing the input coordinates of points with relative distances and angles. Due to the incomple…
One-Shot General Object Localization
Yang You, Zhuochen Miao, Kai Xiong +2
This paper presents a general one-shot object localization algorithm called OneLoc. Current one-shot object localization or detection methods either rely on a slow exhaustive featu…
CPPF++: Uncertainty-Aware Sim2Real Object Pose Estimation by Vote Aggregation
Yang You, Wenhao He, Jin Liu +3
Object pose estimation constitutes a critical area within the domain of 3D vision. While contemporary state-of-the-art methods that leverage real-world pose annotations have demons…
CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wild
Yang You, Ruoxi Shi, Weiming Wang +1
In this paper, we tackle the problem of category-level 9D pose estimation in the wild, given a single RGB-D frame. Using supervised data of real-world 9D poses is tedious and erron…
Understanding Pixel-level 2D Image Semantics with 3D Keypoint Knowledge Engine
Yang You, Chengkun Li, Yujing Lou +5
Pixel-level 2D object semantic understanding is an important topic in computer vision and could help machine deeply understand objects (e.g. functionality and affordance) in our da…
Skeleton Merger: an Unsupervised Aligned Keypoint Detector
Ruoxi Shi, Zhengrong Xue, Yang You +1
Detecting aligned 3D keypoints is essential under many scenarios such as object tracking, shape retrieval and robotics. However, it is generally hard to prepare a high-quality data…
PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features
Yang You, Yujing Lou, Ruoxi Shi +5
Point cloud analysis without pose priors is very challenging in real applications, as the orientations of point clouds are often unknown. In this paper, we propose a brand new poin…
Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes
Yang You, Zelin Ye, Yujing Lou +5
3D object detection has attracted much attention thanks to the advances in sensors and deep learning methods for point clouds. Current state-of-the-art methods like VoteNet regress…
UKPGAN: A General Self-Supervised Keypoint Detector
Yang You, Wenhai Liu, Yanjie Ze +3
Keypoint detection is an essential component for the object registration and alignment. In this work, we reckon keypoint detection as information compression, and force the model t…
Semantic Correspondence via 2D-3D-2D Cycle
Yang You, Chengkun Li, Yujing Lou +4
Visual semantic correspondence is an important topic in computer vision and could help machine understand objects in our daily life. However, most previous methods directly train o…
KeypointNet: A Large-scale 3D Keypoint Dataset Aggregated from Numerous Human Annotations
Yang You, Yujing Lou, Chengkun Li +5
Detecting 3D objects keypoints is of great interest to the areas of both graphics and computer vision. There have been several 2D and 3D keypoint datasets aiming to address this pr…
Human Correspondence Consensus for 3D Object Semantic Understanding
Yujing Lou, Yang You, Chengkun Li +5
Semantic understanding of 3D objects is crucial in many applications such as object manipulation. However, it is hard to give a universal definition of point-level semantics that e…
Combinational Q-Learning for Dou Di Zhu
Yang You, Liangwei Li, Baisong Guo +2
Deep reinforcement learning (DRL) has gained a lot of attention in recent years, and has been proven to be able to play Atari games and Go at or above human levels. However, those…
Pointwise Rotation-Invariant Network with Adaptive Sampling and 3D Spherical Voxel Convolution
Yang You, Yujing Lou, Qi Liu +4
Point cloud analysis without pose priors is very challenging in real applications, as the orientations of point clouds are often unknown. In this paper, we propose a brand new poin…