Coarse Attribute Prediction with Task Agnostic Distillation for Real World Clothes Changing ReID


Priyank Pathak (University of Central Florida), Yogesh S Rawat (University of Central Florida)
The 35th British Machine Vision Conference
PDFSupplementary

Abstract

This work focuses on Clothes Changing Re-IDentification (CC-ReID) for the real world. Existing works perform well with high-quality (HQ) images, but struggle with low-quality (LQ) where we can have artifacts like pixelation, out-of-focus blur, and motion blur. These artifacts introduce noise to not only external biometric attributes (e.g. pose, body shape, etc.) but also corrupt the model’s internal feature representation. Models usually cluster LQ image features together, making it difficult to distinguish between them, leading to incorrect matches. We propose a novel framework Robustness against Low-Quality (RLQ) to improve CC-ReID model on real-world data. RLQ relies on Coarse Attributes Prediction (CAP) and Task Agnostic Distillation (TAD) operating in alternate steps in a novel training mechanism. CAP enriches the model with external fine-grained attributes via coarse predictions, thereby reducing the effect of noisy input. On the other hand, TAD enhances the model’s internal feature representation by bridging the gap between HQ and LQ features, via an external dataset through task-agnostic self-supervision and distillation. Our RLQ is among the few works to successfully learn from external attributes on very low-quality on real-world datasets like LaST, and DeepChange. The code is public on https://github.com/ppriyank/RLQ-CGAL-UBD.

Citation

@inproceedings{Pathak_2025_BMVC,
author    = {Priyank Pathak and Yogesh S Rawat},
title     = {Coarse Attribute Prediction with Task Agnostic Distillation for Real World Clothes Changing ReID},
booktitle = {36th British Machine Vision Conference 2025, {BMVC} 2025, Sheffield, UK, November 24-27, 2025},
publisher = {BMVA},
year      = {2025},
url       = {https://bmva-archive.org.uk/bmvc/2025/assets/papers/Paper_346/paper.pdf}
}


Copyright © 2025 The British Machine Vision Association and Society for Pattern Recognition
The British Machine Vision Conference is organised by The British Machine Vision Association and Society for Pattern Recognition. The Association is a Company limited by guarantee, No.2543446, and a non-profit-making body, registered in England and Wales as Charity No.1002307 (Registered Office: Dept. of Computer Science, Durham University, South Road, Durham, DH1 3LE, UK).

Imprint | Data Protection