Few-Shot Video Object Detection

• URL: http://arxiv.org/abs/2104.14805v1
• Date: Fri, 30 Apr 2021 07:38:04 GMT
• Title: Few-Shot Video Object Detection
• Authors: Qi Fan, Chi-Keung Tang, Yu-Wing Tai
• Abstract summary: We introduce Few-Shot Video Object Detection (FSVOD) with three important contributions. FSVOD-500 comprises of 500 classes with class-balanced videos in each category for few-shot learning. Our TPN and TMN+ are jointly and end-to-end trained.
• Score: 70.43402912344327
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: We introduce Few-Shot Video Object Detection (FSVOD) with three important contributions: 1) a large-scale video dataset FSVOD-500 comprising of 500 classes with class-balanced videos in each category for few-shot learning; 2) a novel Tube Proposal Network (TPN) to generate high-quality video tube proposals to aggregate feature representation for the target video object; 3) a strategically improved Temporal Matching Network (TMN+) to match representative query tube features and supports with better discriminative ability. Our TPN and TMN+ are jointly and end-to-end trained. Extensive experiments demonstrate that our method produces significantly better detection results on two few-shot video object detection datasets compared to image-based methods and other naive video-based extensions. Codes and datasets will be released at https://github.com/fanq15/FewX.

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