Jan 5, 2021 · We propose to leverage weakly-labeled videos from a large dataset using tag retrieval followed by selecting the best clips with visual similarities.
Jul 9, 2020 · We show that this simple baseline approach outperforms prior few-shot video classification methods by over 20 points on existing benchmarks.
A simple 3D CNN baseline is developed, surpassing existing methods by a large margin and proposed to leverage weakly-labeled videos from a large dataset ...
This is a repo covering the following papers. Generalized Few-Shot Video Classification with Video Retrieval and Feature Generation
Few-shot learning methods operate in low data regimes. The aim is to learn with few training examples per class. Although significant progress has been made ...
Few-shot learning methods operate in low data regimes. The aim is to learn with few training examples per class. Although significant progress has been made ...
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Author: Xian, Yongqin et al.; Genre: Conference Paper; Published online: 2020; Title: Generalized Many-Way Few-Shot Video Classification.
Generalized Many-Way Few-Shot Video Classification. Y. Xian, B. Korbar, M. Douze, B. Schiele, Z. Akata, and L. Torresani. ECCV Workshops (6), volume 12540 ...
The goal of few-shot learning is to train a network that can generalize well to novel classes. Specifically, in a n-way, k-shot problem, each episode contains a ...
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