{"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/hard-net-hardness-aware-discrimination","title":"HARD-Net: Hardness-AwaRe Discrimination Network for 3D Early Activity Prediction","arxiv_id":null,"date":"2020-08-01","proceeding":"ECCV 2020 8","authors":["Tianjiao Li","Jun Liu","Wei zhang","Ling-Yu Duan"],"abstract":"Predicting the class label from the partially observed activity sequence is a very hard task, as the observed early segments of different activities can be very similar. In this paper, we propose a novel Hardness-AwaRe Discrimination Network (HARD-Net) to specifically investigate the relationships between the similar activity pairs that are hard to be discriminated. Specifically, a Hard Instance-Interference Class (HI-IC) bank is designed, which dynamically records the hard similar pairs. Based on the HI-IC bank, a novel adversarial learning scheme is proposed to train our HARD-Net, which thus grants our network with the strong capability in mining subtle discrimination information for 3D early activity prediction. We evaluate our proposed HARD-Net on two public activity datasets and achieve state-of-the-art performance.","url_abs":"https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/1360_ECCV_2020_paper.php","url_pdf":"https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123560409.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":[],"tasks":[{"task_slug":"activity-prediction","task_name":"Activity Prediction"},{"task_slug":"skeleton-based-action-recognition","task_name":"Skeleton Based Action Recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/skeleton-based-action-recognition-on-uav","task":"Skeleton Based Action Recognition","dataset":"UAV-Human","model":"HARD-Net","rank_in_archive_order":6,"of":9,"metrics":{"CSv1(%)":"36.97"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}