activity
20182022
most citedGeneAnnotator: A Semi-automatic Annotation Tool for Visual Scene Graph

6 citations · 13 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV20222 cited

Dual Clustering Co-teaching with Consistent Sample Mining for Unsupervised Person Re-Identification

Zeqi Chen, Zhichao Cui, Chi Zhang +2

In unsupervised person Re-ID, peer-teaching strategy leveraging two networks to facilitate training has been proven to be an effective method to deal with the pseudo label noise. H…

cs.CV20216 cited

GeneAnnotator: A Semi-automatic Annotation Tool for Visual Scene Graph

Zhixuan Zhang, Chi Zhang, Zhenning Niu +2

In this manuscript, we introduce a semi-automatic scene graph annotation tool for images, the GeneAnnotator. This software allows human annotators to describe the existing relation…

cs.IR20203 cited

PyRetri: A PyTorch-based Library for Unsupervised Image Retrieval by Deep Convolutional Neural Networks

Benyi Hu, Ren-Jie Song, Xiu-Shen Wei +3

Despite significant progress of applying deep learning methods to the field of content-based image retrieval, there has not been a software library that covers these methods in a u…

cs.CV2019

Bimodal Stereo: Joint Shape and Pose Estimation from Color-Depth Image Pair

Chi Zhang, Yuehu Liu, Ying Wu +2

Mutual calibration between color and depth cameras is a challenging topic in multi-modal data registration. In this paper, we are confronted with a "Bimodal Stereo" problem, which…

cs.CV20192 cited

Joint haze image synthesis and dehazing with mmd-vae losses

Zongliang Li, Chi Zhang, Gaofeng Meng +1

Fog and haze are weathers with low visibility which are adversarial to the driving safety of intelligent vehicles equipped with optical sensors like cameras and LiDARs. Therefore i…

cs.CV2018

Spatio-Temporal Road Scene Reconstruction using Superpixel Markov Random Field

Yaochen Li, Yuehu Liu, Jihua Zhu +3

Scene model construction based on image rendering is an indispensable but challenging technique in computer vision and intelligent transportation systems. In this paper, we propose…