activity
20182021
most citedCombinational Q-Learning for Dou Di Zhu

5 citations · 6 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CV20211 cited

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…

cs.CV2020

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…

cs.CV2020

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…

cs.CV2019

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…

cs.LG20195 cited

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…

cs.CV2018

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…