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Open-set multi-view seahorse re-identification from underwater photograph sequences

Paper recorded by Signals 4 on 2026-10-29 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.CV · 计算机视觉 · first seen 2026-10-30

Abstract

Automated animal re-identification from photograph sequences can facilitate minimally invasive Capture-Mark-Recapture studies at scale. Yet, photographs taken during an observation session can vary greatly in quality, not always providing the necessary information for accurate re-identification. In this paper, we present new methods for taxonomic classification, sex determination, and open-set re-

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#79 most recent of 710 cs.CV papers we have recorded · ↑ newer: M-PFT: Angular Margin for Calibrated Prompt-Tuning of Fine-Tuned Visio · ↓ older: LiDAR-SHIELD: A Fully Dockerized Adversarial Robustness Assessment Fra
Cite this page: Open-set multi-view seahorse re-identification from underwater photograph sequences: the #79 most recent of 710 cs.CV papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/open-set-multi-view-seahorse-re-identification-from-underwater-photograph-sequen.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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