activity
20182022
most citedDeep Texture-Aware Features for Camouflaged Object Detection

32 citations · 46 across the 8 of their papers we have counts for

collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV2022

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…

cs.CV20222 cited

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…

cs.CV202132 cited

Deep Texture-Aware Features for Camouflaged Object Detection

Jingjing Ren, Xiaowei Hu, Lei Zhu +5

Camouflaged object detection is a challenging task that aims to identify objects having similar texture to the surroundings. This paper presents to amplify the subtle texture diffe…

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…