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3D Visual saliency: an independent perceptual measure or a derivative of 2d image saliency?

Song, Ran, Zhang, Wei, Zhao, Yitian, Liu, Yonghuai and Rosin, Paul L. ORCID: 2023. 3D Visual saliency: an independent perceptual measure or a derivative of 2d image saliency? IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (11) , pp. 13083-13099. 10.1109/TPAMI.2023.3287356

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While 3D visual saliency aims to predict regional importance of 3D surfaces in agreement with human visual perception and has been well researched in computer vision and graphics, latest work with eye-tracking experiments shows that state-of-the-art 3D visual saliency methods remain poor at predicting human fixations. Cues emerging prominently from these experiments suggest that 3D visual saliency might associate with 2D image saliency. This paper proposes a framework that combines a Generative Adversarial Network and a Conditional Random Field for learning visual saliency of both a single 3D object and a scene composed of multiple 3D objects with image saliency ground truth to 1) investigate whether 3D visual saliency is an independent perceptual measure or just a derivative of image saliency and 2) provide a weakly supervised method for more accurately predicting 3D visual saliency. Through extensive experiments, we not only demonstrate that our method significantly outperforms the state-of-the-art approaches, but also manage to answer the interesting and worthy question proposed within the title of this paper

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Institute of Electrical and Electronics Engineers
ISSN: 0162-8828
Date of First Compliant Deposit: 21 June 2023
Date of Acceptance: 15 June 2023
Last Modified: 06 Nov 2023 18:07

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