Ponce-Lopez, V;
Burghardt, T;
Sun, Y;
Hannuna, S;
Damen, D;
Mirmehdi, M;
(2019)
Deep Compact Person Re-Identification with Distractor Synthesis via Guided DC-GANs.
In: Ricci, E and Bulo, SR and Snoek, C and Lanz, O and Messelodi, S and Sebe, N, (eds.)
Image Analysis and Processing – ICIAP 2019. ICIAP 2019.
(pp. pp. 488-498).
Springer: Cham, Switzerland.
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Abstract
We present a dual-stream CNN that learns both appearance and facial features in tandem from still images and, after feature fusion, infers person identities. We then describe an alternative architecture of a single, lightweight ID-CondenseNet where a face detector-guided DC-GAN is used to generate distractor person images for enhanced training. For evaluation, we test both architectures on FLIMA, a new extension of an existing person re-identification dataset with added frame-by-frame annotations of face presence. Although the dual-stream CNN can outperform the CondenseNet approach on FLIMA, we show that the latter surpasses all state-of-the-art architectures in top-1 ranking performance when applied to the largest existing person re-identification dataset, MSMT17. We conclude that whilst re-identification performance is highly sensitive to the structure of datasets, distractor augmentation and network compression have a role to play for enhancing performance characteristics for larger scale applications.
| Type: | Proceedings paper |
|---|---|
| Title: | Deep Compact Person Re-Identification with Distractor Synthesis via Guided DC-GANs |
| Event: | 20th International Conference on Image Analysis and Processing (ICIAP) |
| Location: | Univ Trento, Fac Law, Trento, ITALY |
| Dates: | 09 September 2019 - 13 September 2019 |
| ISBN-13: | 978-3-030-30641-0 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-030-30642-7_44 |
| Publisher version: | https://doi.org/10.1007/978-3-030-30642-7_44 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Person Re-ID, GANs, Distractor synthesis, Deep face analysis |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10115347 |
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