Discriminative Pedestrian Features and Gated Channel Attention for Clothes-Changing Person Re-Identification
Not on the map. Why?
Abstract (arXiv)
In public safety and social life, the task of Clothes-Changing Person Re-Identification (CC-ReID) has become increasingly significant. However, this task faces considerable challenges due to appearance changes caused by clothing alterations. Addressing this issue, this paper proposes an innovative method for disentangled feature extraction, effectively extracting discriminative features from pedestrian images that are invariant to clothing. This method leverages pedestrian parsing techniques to identify and retain features closely associated with individual identity while disregarding the variable nature of clothing attributes. Furthermore, this study introduces a gated channel attention mechanism, which, by adjusting the network's focus, aids the model in more effectively learning and emphasizing features critical for pedestrian identity recognition. Extensive experiments conducted on two standard CC-ReID datasets validate the effectiveness of the proposed approach, with performance surpassing current leading solutions. The Top-1 accuracy under clothing change scenarios on the PRCC and VC-Clothes datasets reached 64.8% and 83.7%, respectively.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 16 of its 25 references that are in the map. First posted on arXiv 29 Oct 2024.
Builds on
16 of 25 references.
References · 16
- 2015Deep Residual Learning for Image Recognitioncited by 51,809
- 2014Adam: A Method for Stochastic Optimizationcited by 36,960
- 2017Random Erasing Data Augmentationcited by 1,235
- 2017In Defense of the Triplet Loss for Person Re-Identificationcited by 784
- 2019ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networkscited by 572
- 2017Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)cited by 472
- 2021TransReID: Transformer-based Object Re-Identificationcited by 432
- 2019Self-Correction for Human Parsingcited by 179
- 2020Identity-Guided Human Semantic Parsing for Person Re-Identificationcited by 118
- 2017Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsingcited by 109
- 2022Clothes-Changing Person Re-identification with RGB Modality Onlycited by 98
- 2020Person Re-identification by Contour Sketch under Moderate Clothing Changecited by 91
4 more
- 2020Long-Term Cloth-Changing Person Re-identificationcited by 85
- 2019Interaction-and-Aggregation Network for Person Re-identificationcited by 80
- 2021Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and Regularizationcited by 69
- 2020When Person Re-identification Meets Changing Clothescited by 51
Built on by
Not cited yet.