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20172021
most citedAlignedReID: Surpassing Human-Level Performance in Person Re-Identification

439 citations · 686 across the 8 of their papers we have counts for

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14 papers · 1 filter

cs.CV202195 cited

TransReID: Transformer-based Object Re-Identification

Shuting He, Hao Luo, Pichao Wang +3

Extracting robust feature representation is one of the key challenges in object re-identification (ReID). Although convolution neural network (CNN)-based methods have achieved grea…

cs.CV2021

COTR: Correspondence Transformer for Matching Across Images

Wei Jiang, Eduard Trulls, Jan Hosang +2

We propose a novel framework for finding correspondences in images based on a deep neural network that, given two images and a query point in one of them, finds its correspondence…

cs.CV20204 cited

1st Place Solution to VisDA-2020: Bias Elimination for Domain Adaptive Pedestrian Re-identification

Jianyang Gu, Hao Luo, Weihua Chen +6

This paper presents our proposed methods for domain adaptive pedestrian re-identification (Re-ID) task in Visual Domain Adaptation Challenge (VisDA-2020). Considering the large gap…

cs.CV20205 cited

SMAP: Single-Shot Multi-Person Absolute 3D Pose Estimation

Jianan Zhen, Qi Fang, Jiaming Sun +4

Recovering multi-person 3D poses with absolute scales from a single RGB image is a challenging problem due to the inherent depth and scale ambiguity from a single view. Addressing…

cs.CV20205 cited

Multi-Domain Learning and Identity Mining for Vehicle Re-Identification

Shuting He, Hao Luo, Weihua Chen +5

This paper introduces our solution for the Track2 in AI City Challenge 2020 (AICITY20). The Track2 is a vehicle re-identification (ReID) task with both the real-world data and synt…

cs.CV202014 cited

Cross-Spectrum Dual-Subspace Pairing for RGB-infrared Cross-Modality Person Re-Identification

Xing Fan, Hao Luo, Chi Zhang +1

Due to its potential wide applications in video surveillance and other computer vision tasks like tracking, person re-identification (ReID) has become popular and been widely inves…