AI
IIT Patna at "ICPR 2026 TVRID Competition on Privacy-Preserving Person Re-Identification from Top-View RGB-Depth Camera"
Publication: cs.AI updates on arXiv.org
Author: Abhinav Kumar, Swagatam Pati, Advait Deshmukh, Aditya Mehrotra, Bibek Das, Kumari Priya, Utsav Kumar Nareti, Saba Akram, Chandranath Adak
Source published: 11/11/2026, 05:00:00 UTC
Briefing created: 11/11/2026, 07:05:48 UTC
Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 11/11/2026, 05:03:25 UTC.
Briefings
IIT Patna teams 'abhinavkumar03' and 'sjkdgfhl_' placed 5th and 7th in the ICPR 2026 TVRID competition, achieving 93.51% mAP and 99.63% RGB mAP respectively. Their methods significantly outperformed the 57.19% track-average Depth mAP, demonstrating the critical role of depth representation in privacy-preserving person re-identification.
Key points
- Two IIT Patna teams achieved top-10 rankings in the ICPR 2026 TVRID competition, with 'abhinavkumar03' securing 93.51% mAP on Depth and 'sjkdgfhl_' reaching 99.63% on RGB.
- The competition evaluated 86 identities using four synchronized Intel RealSense D455 cameras across multiple viewpoints, measuring performance via mAP and CMC@1 metrics.
Context
The ICPR 2026 TVRID competition focused on privacy-preserving person re-identification using top-view RGB-Depth cameras, replacing frontal appearance with anthropometric shape and depth sensing. IIT Patna's participation highlights the competitive landscape of this emerging privacy-focused technology.
Limitations
Results are limited to the ICPR 2026 TVRID competition context with 86 identities and four synchronized cameras. Specific team performance details are derived from the arXiv preprint, and the study does not address broader privacy implications or real-world deployment scenarios.
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