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Learning Saliency From Fixations.

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Dublin City University Participation in the VTT Track at TRECVid 2017., , , , , , , , и . TRECVID, National Institute of Standards and Technology (NIST), (2017)SalGAN: Visual Saliency Prediction with Generative Adversarial Networks, , , , , , и . (2017)cite arxiv:1701.01081Comment: Our results can be reproduced with the source code and trained models available at https://imatge-upc.github.io/saliency-salgan-2017/.People, Penguins and Petri Dishes: Adapting Object Counting Models To New Visual Domains And Object Types Without Forgetting., , , , и . CoRR, (2017)Holistic features for real-time crowd behaviour anomaly detection., , , и . ICIP, стр. 918-922. IEEE, (2016)PathGAN: Visual Scanpath Prediction with Generative Adversarial Networks., , , и . ECCV Workshops (5), том 11133 из Lecture Notes in Computer Science, стр. 406-422. Springer, (2018)Bags of Local Convolutional Features for Scalable Instance Search., , , , , и . ICMR, стр. 327-331. ACM, (2016)ATSal: An Attention Based Architecture for Saliency Prediction in 360 Videos., , , и . CoRR, (2020)Domain Randomization for Object Counting., , , и . AICS, том 3105 из CEUR Workshop Proceedings, стр. 25-35. CEUR-WS.org, (2021)How important are faces for person re-identification?, , , и . ICPR, стр. 6912-6919. IEEE, (2020)FastSal: a Computationally Efficient Network for Visual Saliency Prediction., и . ICPR, стр. 9054-9061. IEEE, (2020)