GazeHTA: End-to-end Gaze Target Detection with Head-Target Association

• URL: http://arxiv.org/abs/2404.10718v2
• Date: Fri, 19 Apr 2024 01:19:25 GMT
• Title: GazeHTA: End-to-end Gaze Target Detection with Head-Target Association
• Authors: Zhi-Yi Lin, Jouh Yeong Chew, Jan van Gemert, Xucong Zhang,
• Abstract summary: We propose an end-to-end approach for gaze target detection: predicting a head-target connection between individuals and the target image regions they are looking at. Most of the existing methods use independent components such as off-the-shelf head detectors or have problems in establishing associations between heads and gaze targets. We investigate an end-to-end multi-person Gaze target detection framework with Heads and Targets Association (GazeHTA), which predicts multiple head-target instances based solely on input scene image.
• Score: 12.38704128536528
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose an end-to-end approach for gaze target detection: predicting a head-target connection between individuals and the target image regions they are looking at. Most of the existing methods use independent components such as off-the-shelf head detectors or have problems in establishing associations between heads and gaze targets. In contrast, we investigate an end-to-end multi-person Gaze target detection framework with Heads and Targets Association (GazeHTA), which predicts multiple head-target instances based solely on input scene image. GazeHTA addresses challenges in gaze target detection by (1) leveraging a pre-trained diffusion model to extract scene features for rich semantic understanding, (2) re-injecting a head feature to enhance the head priors for improved head understanding, and (3) learning a connection map as the explicit visual associations between heads and gaze targets. Our extensive experimental results demonstrate that GazeHTA outperforms state-of-the-art gaze target detection methods and two adapted diffusion-based baselines on two standard datasets.

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