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20182020
most citedJointly Adversarial Network to Wavelength Compensation and Dehazing of Underwater Images

15 citations · 37 across the 14 of their papers we have counts for

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14 papers · 1 filter

cs.CV20203 cited

Unsupervised Vehicle Re-identification with Progressive Adaptation

Jinjia Peng, Yang Wang, Huibing Wang +3

Vehicle re-identification (reID) aims at identifying vehicles across different non-overlapping cameras views. The existing methods heavily relied on well-labeled datasets for ideal…

cs.CV2020

Discriminative Feature and Dictionary Learning with Part-aware Model for Vehicle Re-identification

Huibing Wang, Jinjia Peng, Guangqi Jiang +2

With the development of smart cities, urban surveillance video analysis will play a further significant role in intelligent transportation systems. Identifying the same target vehi…

cs.CV20201 cited

Purifying Real Images with an Attention-guided Style Transfer Network for Gaze Estimation

Yuxiao Yan, Yang Yan, Jinjia Peng +2

Recently, the progress of learning-by-synthesis has proposed a training model for synthetic images, which can effectively reduce the cost of human and material resources. However,…

cs.CV20209 cited

Attribute-guided Feature Learning Network for Vehicle Re-identification

Huibing Wang, Jinjia Peng, Dongyan Chen +3

Vehicle re-identification (reID) plays an important role in the automatic analysis of the increasing urban surveillance videos, which has become a hot topic in recent years. Howeve…

cs.CV20194 cited

Eliminating cross-camera bias for vehicle re-identification

Jinjia Peng, Guangqi Jiang, Dongyan Chen +3

Vehicle re-identification (reID) often requires recognize a target vehicle in large datasets captured from multi-cameras. It plays an important role in the automatic analysis of th…

cs.CV2019

Graph-based Multi-view Binary Learning for Image Clustering

Guangqi Jiang, Huibing Wang, Jinjia Peng +2

Hashing techniques, also known as binary code learning, have recently gained increasing attention in large-scale data analysis and storage. Generally, most existing hash clustering…