activity
20182020
most citedPCPL: Predicate-Correlation Perception Learning for Unbiased Scene Graph Generation

114 citations · 119 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2020114 cited

PCPL: Predicate-Correlation Perception Learning for Unbiased Scene Graph Generation

Shaotian Yan, Chen Shen, Zhongming Jin +4

Today, scene graph generation(SGG) task is largely limited in realistic scenarios, mainly due to the extremely long-tailed bias of predicate annotation distribution. Thus, tackling…

cs.CV20202 cited

SLV: Spatial Likelihood Voting for Weakly Supervised Object Detection

Ze Chen, Zhihang Fu, Rongxin Jiang +2

Based on the framework of multiple instance learning (MIL), tremendous works have promoted the advances of weakly supervised object detection (WSOD). However, most MIL-based method…

eess.IV20193 cited

AIM 2019 Challenge on Image Demoireing: Methods and Results

Shanxin Yuan, Radu Timofte, Gregory Slabaugh +25

This paper reviews the first-ever image demoireing challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ICCV 2019. This paper desc…

cs.CV2018

S-Net: A Scalable Convolutional Neural Network for JPEG Compression Artifact Reduction

Bolun Zheng, Rui Sun, Xiang Tian +1

Recent studies have used deep residual convolutional neural networks (CNNs) for JPEG compression artifact reduction. This study proposes a scalable CNN called S-Net. Our approach e…

cs.CV2018

Implicit Dual-domain Convolutional Network for Robust Color Image Compression Artifact Reduction

Bolun Zheng, Yaowu Chen, Xiang Tian +2

Several dual-domain convolutional neural network-based methods show outstanding performance in reducing image compression artifacts. However, they suffer from handling color images…

cs.CV2018

Sharp Attention Network via Adaptive Sampling for Person Re-identification

Chen Shen, Guo-Jun Qi, Rongxin Jiang +4

In this paper, we present novel sharp attention networks by adaptively sampling feature maps from convolutional neural networks (CNNs) for person re-identification (re-ID) problem.…