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{ "pk": 27868, "title": "Same-different problems strain covolutional neural networks", "subtitle": null, "abstract": "The robust and efficient recognition of visual relations in im-ages is a hallmark of biological vision. We argue that, de-spite recent progress in visual recognition, modern machinevision algorithms are severely limited in their ability to learnvisual relations. Through controlled experiments, we demon-strate that visual-relation problems strain convolutional neuralnetworks (CNNs). The networks eventually break altogetherwhen rote memorization becomes impossible, as when intra-class variability exceeds network capacity. Motivated by thecomparable success of biological vision, we argue that feed-back mechanisms including attention and perceptual groupingmay be the key computational components underlying abstractvisual reasoning.", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [ { "word": "Visual relations" }, { "word": "Convolutional Neural Networks" }, { "word": "Deep learning" }, { "word": "Visual attentino" }, { "word": "Perceptual Grouping" } ], "section": "Publication-based-Talks", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/9zz2g6g1", "frozenauthors": [ { "first_name": "Mathew", "middle_name": "", "last_name": "Ricci", "name_suffix": "", "institution": "Brown", "department": "" }, { "first_name": "Junkyung", "middle_name": "", "last_name": "Kim", "name_suffix": "", "institution": "Brown", "department": "" }, { "first_name": "Thomas", "middle_name": "", "last_name": "Serre", "name_suffix": "", "institution": "Brown", "department": "" } ], "date_submitted": null, "date_accepted": null, "date_published": "2018-01-01T18:00:00Z", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27868/galley/17506/download/" } ] }