Category Query Learning for Human-Object Interaction Classification

• URL: http://arxiv.org/abs/2303.14005v1
• Date: Fri, 24 Mar 2023 13:59:58 GMT
• Title: Category Query Learning for Human-Object Interaction Classification
• Authors: Chi Xie, Fangao Zeng, Yue Hu, Shuang Liang and Yichen Wei
• Abstract summary: Unlike most previous HOI methods, we propose a novel and complementary approach called category query learning. This idea is motivated by an earlier multi-label image classification method, but is for the first time applied for the challenging human-object interaction classification task. Our method is simple, general and effective. It is validated on three representative HOI baselines and achieves new state-of-the-art results on two benchmarks.
• Score: 25.979131884959923
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Unlike most previous HOI methods that focus on learning better human-object features, we propose a novel and complementary approach called category query learning. Such queries are explicitly associated to interaction categories, converted to image specific category representation via a transformer decoder, and learnt via an auxiliary image-level classification task. This idea is motivated by an earlier multi-label image classification method, but is for the first time applied for the challenging human-object interaction classification task. Our method is simple, general and effective. It is validated on three representative HOI baselines and achieves new state-of-the-art results on two benchmarks.

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