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Few-Shot Video Recognition via Hierarchical Metric Learning

Paper recorded by Signals 4 on 2026-09-04 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07

Category: cs.CV · 计算机视觉 · first seen 2026-09-07

Abstract

Few-shot action recognition (FSAR) aims to recognize unseen action categories with only a small number of annotated video samples. Recent works typically apply single-prototype supervision at the network output and fail to sufficiently exploit rich cross-frame global spatial information in videos. Even existing multi-level metric schemes only impose parallel prototype constraints on intermediate l

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#138 most recent of 237 cs.CV papers we have recorded · ↑ newer: Compact Neural Appearance Models for Efficient Gaussian Splatting · ↓ older: Cross-Domain Tracker Adaptation Without Target-Domain Labels via Visio
Cite this page: Few-Shot Video Recognition via Hierarchical Metric Learning: the #138 most recent of 237 cs.CV papers we have recorded (as of 2026-09-04). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/few-shot-video-recognition-via-hierarchical-metric-learning.html
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