{"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/cross-and-learn-cross-modal-self-supervision","title":"Cross and Learn: Cross-Modal Self-Supervision","arxiv_id":"1811.03879","date":"2018-11-09","proceeding":null,"authors":["Nawid Sayed","Biagio Brattoli","Björn Ommer"],"abstract":"In this paper we present a self-supervised method for representation learning\nutilizing two different modalities. Based on the observation that cross-modal\ninformation has a high semantic meaning we propose a method to effectively\nexploit this signal. For our approach we utilize video data since it is\navailable on a large scale and provides easily accessible modalities given by\nRGB and optical flow. We demonstrate state-of-the-art performance on highly\ncontested action recognition datasets in the context of self-supervised\nlearning. We show that our feature representation also transfers to other tasks\nand conduct extensive ablation studies to validate our core contributions. Code\nand model can be found at https://github.com/nawidsayed/Cross-and-Learn.","url_abs":"http://arxiv.org/abs/1811.03879v3","url_pdf":"http://arxiv.org/pdf/1811.03879v3.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":"cross-and-learn-cross-modal-self-supervision","repo_url":"https://github.com/nawidsayed/Cross-and-Learn","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"action-recognition-in-videos","task_name":"Action Recognition"},{"task_slug":"optical-flow-estimation","task_name":"Optical Flow Estimation"},{"task_slug":"representation-learning","task_name":"Representation Learning"},{"task_slug":"self-supervised-learning","task_name":"Self-Supervised Learning"},{"task_slug":"action-recognition","task_name":"Temporal Action Localization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1811.03879","atlas_url":"https://app.syntology.ai/?focus=1811.03879","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}