{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/after-all-only-the-last-neuron-matters","title":"After All, Only The Last Neuron Matters: Comparing Multi-modal Fusion Functions for Scene Graph Generation","arxiv_id":"2011.04779","date":"2020-11-09","proceeding":null,"authors":["Mohamed Karim Belaid"],"abstract":"From object segmentation to word vector representations, Scene Graph Generation (SGG) became a complex task built upon numerous research results. In this paper, we focus on the last module of this model: the fusion function. The role of this latter is to combine three hidden states. We perform an ablation test in order to compare different implementations. First, we reproduce the state-of-the-art results using SUM, and GATE functions. Then we expand the original solution by adding more model-agnostic functions: an adapted version of DIST and a mixture between MFB and GATE. On the basis of the state-of-the-art configuration, DIST performed the best Recall @ K, which makes it now part of the state-of-the-art.","url_abs":"https://arxiv.org/abs/2011.04779v1","url_pdf":"https://arxiv.org/pdf/2011.04779v1.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":"after-all-only-the-last-neuron-matters","repo_url":"https://github.com/Karim-53/SGG","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"all","task_name":"All"},{"task_slug":"graph-generation","task_name":"Graph Generation"},{"task_slug":"scene-graph-generation","task_name":"Scene Graph Generation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}