{"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/time-mapping-using-space-time-saliency","title":"Time-Mapping Using Space-Time Saliency","arxiv_id":null,"date":"2014-06-01","proceeding":"CVPR 2014 6","authors":["Feng Zhou","Sing Bing Kang","Michael F. Cohen"],"abstract":"We describe a new approach for generating regular-speed, low-frame-rate (LFR) video from a high-frame-rate (HFR) input while preserving the important moments in the original. We call this time-mapping, a time-based analogy to high dynamic range to low dynamic range spatial tone-mapping. Our approach makes these contributions: (1) a robust space-time saliency method for evaluating visual importance, (2) a re-timing technique to temporally resample based on frame importance, and (3) temporal filters to enhance the rendering of salient motion. Results of our space-time saliency method on a benchmark dataset show it is state-of-the-art. In addition, the benefits of our approach to HFR-to-LFR time-mapping over more direct methods are demonstrated in a user study.","url_abs":"http://openaccess.thecvf.com/content_cvpr_2014/html/Zhou_Time-Mapping_Using_Space-Time_2014_CVPR_paper.html","url_pdf":"http://openaccess.thecvf.com/content_cvpr_2014/papers/Zhou_Time-Mapping_Using_Space-Time_2014_CVPR_paper.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":"tone-mapping","task_name":"Tone Mapping"},{"task_slug":"video-salient-object-detection","task_name":"Video Salient Object Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/video-salient-object-detection-on-davis-2016","task":"Video Salient Object Detection","dataset":"DAVIS-2016","model":"TIMP","rank_in_archive_order":10,"of":11,"metrics":{"AVERAGE MAE":"0.185","MAX E-MEASURE":"0.680","S-Measure":"0.574"},"uses_additional_data":true},{"leaderboard":"/sota/video-salient-object-detection-on-davsod-2","task":"Video Salient Object Detection","dataset":"DAVSOD-Difficult20","model":"TIMP","rank_in_archive_order":6,"of":8,"metrics":{"Average MAE":"0.190","S-Measure":"0.530","max E-measure":"0.665"},"uses_additional_data":true},{"leaderboard":"/sota/video-salient-object-detection-on-davsod-1","task":"Video Salient Object Detection","dataset":"DAVSOD-Normal25","model":"TIMP","rank_in_archive_order":7,"of":8,"metrics":{"Average MAE":"0.245","S-Measure":"0.503","max E-measure":"0.616"},"uses_additional_data":true},{"leaderboard":"/sota/video-salient-object-detection-on-davsod","task":"Video Salient Object Detection","dataset":"DAVSOD-easy35","model":"TIMP","rank_in_archive_order":8,"of":9,"metrics":{"Average MAE":"0.206","S-Measure":"0.534","max E-Measure":"0.582"},"uses_additional_data":true},{"leaderboard":"/sota/video-salient-object-detection-on-fbms-59","task":"Video Salient Object Detection","dataset":"FBMS-59","model":"TIMP","rank_in_archive_order":16,"of":16,"metrics":{"AVERAGE MAE":"0.192","MAX F-MEASURE":"0.465","S-Measure":"0.576"},"uses_additional_data":true},{"leaderboard":"/sota/video-salient-object-detection-on-uvsd","task":"Video Salient Object Detection","dataset":"UVSD","model":"TIMP","rank_in_archive_order":8,"of":8,"metrics":{"Average MAE":"0.171","S-Measure":"0.541","max E-measure":"0.662"},"uses_additional_data":true},{"leaderboard":"/sota/video-salient-object-detection-on-vos-t","task":"Video Salient Object Detection","dataset":"VOS-T","model":"TIMP","rank_in_archive_order":9,"of":9,"metrics":{"Average MAE":"0.192","S-Measure":"0.546","max E-measure":"0.640"},"uses_additional_data":true},{"leaderboard":"/sota/video-salient-object-detection-on-visal","task":"Video Salient Object Detection","dataset":"ViSal","model":"TIMP","rank_in_archive_order":10,"of":10,"metrics":{"Average MAE":"0.170","S-Measure":"0.612","max E-measure":"0.743"},"uses_additional_data":true}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}