{"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/bipoco-bi-directional-trajectory-prediction","title":"BiPOCO: Bi-Directional Trajectory Prediction with Pose Constraints for Pedestrian Anomaly Detection","arxiv_id":"2207.02281","date":"2022-07-05","proceeding":null,"authors":["Asiegbu Miracle Kanu-Asiegbu","Ram Vasudevan","Xiaoxiao Du"],"abstract":"We present BiPOCO, a Bi-directional trajectory predictor with POse COnstraints, for detecting anomalous activities of pedestrians in videos. In contrast to prior work based on feature reconstruction, our work identifies pedestrian anomalous events by forecasting their future trajectories and comparing the predictions with their expectations. We introduce a set of novel compositional pose-based losses with our predictor and leverage prediction errors of each body joint for pedestrian anomaly detection. Experimental results show that our BiPOCO approach can detect pedestrian anomalous activities with a high detection rate (up to 87.0%) and incorporating pose constraints helps distinguish normal and anomalous poses in prediction. This work extends current literature of using prediction-based methods for anomaly detection and can benefit safety-critical applications such as autonomous driving and surveillance. Code is available at https://github.com/akanuasiegbu/BiPOCO.","url_abs":"https://arxiv.org/abs/2207.02281v1","url_pdf":"https://arxiv.org/pdf/2207.02281v1.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":"bipoco-bi-directional-trajectory-prediction","repo_url":"https://github.com/akanuasiegbu/bipoco","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"GPL-3.0"}}],"tasks":[{"task_slug":"anomaly-detection","task_name":"Anomaly Detection"},{"task_slug":"autonomous-driving","task_name":"Autonomous Driving"},{"task_slug":"prediction","task_name":"Prediction"},{"task_slug":"trajectory-prediction","task_name":"Trajectory Prediction"},{"task_slug":"video-anomaly-detection","task_name":"Video Anomaly Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/anomaly-detection-on-ubnormal","task":"Anomaly Detection","dataset":"UBnormal","model":"BiPOCO","rank_in_archive_order":13,"of":14,"metrics":{"AUC":"50.7"},"uses_additional_data":false},{"leaderboard":"/sota/video-anomaly-detection-on-hr-avenue","task":"Video Anomaly Detection","dataset":"HR-Avenue","model":"BiPOCO","rank_in_archive_order":6,"of":11,"metrics":{"AUC":"87.0"},"uses_additional_data":false},{"leaderboard":"/sota/video-anomaly-detection-on-hr-shanghaitech","task":"Video Anomaly Detection","dataset":"HR-ShanghaiTech","model":"BiPOCO","rank_in_archive_order":11,"of":14,"metrics":{"AUC":"74.9"},"uses_additional_data":false},{"leaderboard":"/sota/video-anomaly-detection-on-hr-ubnormal","task":"Video Anomaly Detection","dataset":"HR-UBnormal","model":"BiPOCO","rank_in_archive_order":8,"of":8,"metrics":{"AUC":"52.3"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2207.02281","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2207.02281"}},"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. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"deterministic:regex_extraction","url":"https://github.com/akanuasiegbu/BiPOCO","reach":{"status":"ok","spdx":"GPL-3.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/akanuasiegbu/bipoco","reach":{"status":"ok","spdx":"GPL-3.0"}}],"summary":{"ran_fixture":1,"ran_honours":1},"by_repo_kind":{"official":{"samples":2,"ran":2,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":2,"samples":[{"code_sha256_prefix":"8dd6f5069cc62fe5","entry":"anomaly_metric","repo":"akanuasiegbu/bipoco","repo_kind":"official","path":"custom_functions/anomaly_detection.py","file_url":"https://github.com/akanuasiegbu/bipoco/blob/HEAD/custom_functions/anomaly_detection.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"GPL-3.0","inline_ok":false,"mcp_get_code":{"code_sha256":"8dd6f5069cc62fe5"}},{"code_sha256_prefix":"5f78cc0b34c2b5db","entry":"xywh_tlbr","repo":"akanuasiegbu/bipoco","repo_kind":"official","path":"custom_functions/anomaly_detection.py","file_url":"https://github.com/akanuasiegbu/bipoco/blob/HEAD/custom_functions/anomaly_detection.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"GPL-3.0","inline_ok":false,"mcp_get_code":{"code_sha256":"5f78cc0b34c2b5db"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}