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arXiv · 2307.09662

Object-aware Gaze Target Detection

Francesco Tonini·Nicola Dall'Asen·Cigdem Beyan·Elisa Ricci
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Abstract

Gaze target detection aims to predict the image location where the person is looking and the probability that a gaze is out of the scene. Several works have tackled this task by regressing a gaze heatmap centered on the gaze location, however, they overlooked decoding the relationship between the people and the gazed objects. This paper proposes a Transformer-based architecture that automatically detects objects (including heads) in the scene to build associations between every head and the gazed-head/object, resulting in a comprehensive, explainable gaze analysis composed of: gaze target area, gaze pixel point, the class and the image location of the gazed-object. Upon evaluation of the in-the-wild benchmarks, our method achieves state-of-the-art results on all metrics (up to 2.91% gain in AUC, 50% reduction in gaze distance, and 9% gain in out-of-frame average precision) for gaze target detection and 11-13% improvement in average precision for the classification and the localization of the gazed-objects. The code of the proposed method is publicly available.

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Francesco Tonini, Nicola Dall'Asen, Cigdem Beyan, Elisa Ricci. 2023-09-27. Object-aware Gaze Target Detection. https://arxiv.org/abs/2307.09662

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