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However, since the distribution of real-world\nrelationships is seriously unbalanced, existing methods perform quite poorly\nfor the less frequent relationships. In this work, we find that the statistical\ncorrelations between object pairs and their relationships can effectively\nregularize semantic space and make prediction less ambiguous, and thus well\naddress the unbalanced distribution issue. To achieve this, we incorporate\nthese statistical correlations into deep neural networks to facilitate scene\ngraph generation by developing a Knowledge-Embedded Routing Network. More\nspecifically, we show that the statistical correlations between objects\nappearing in images and their relationships, can be explicitly represented by a\nstructured knowledge graph, and a routing mechanism is learned to propagate\nmessages through the graph to explore their interactions. Extensive experiments\non the large-scale Visual Genome dataset demonstrate the superiority of the\nproposed method over current state-of-the-art competitors.","url_abs":"http://arxiv.org/abs/1903.03326v1","url_pdf":"http://arxiv.org/pdf/1903.03326v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"knowledge-embedded-routing-network-for-scene","repo_url":"https://github.com/yuweihao/KERN","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"knowledge-embedded-routing-network-for-scene","repo_url":"https://github.com/HCPLab-SYSU/KERN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"knowledge-embedded-routing-network-for-scene","repo_url":"https://github.com/ZhecanJamesWang/GLAT_SGG","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"graph-generation","task_name":"Graph Generation"},{"task_slug":"scene-graph-generation","task_name":"Scene Graph Generation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/scene-graph-generation-on-visual-genome","task":"Scene Graph Generation","dataset":"Visual Genome","model":"KERN","rank_in_archive_order":9,"of":19,"metrics":{"Recall@50":"27.1"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1903.03326","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1903.03326"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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