{"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/stochastic-video-generation-with-a-learned","title":"Stochastic Video Generation with a Learned Prior","arxiv_id":"1802.07687","date":"2018-02-21","proceeding":"ICML 2018 7","authors":["Emily Denton","Rob Fergus"],"abstract":"Generating video frames that accurately predict future world states is\nchallenging. Existing approaches either fail to capture the full distribution\nof outcomes, or yield blurry generations, or both. In this paper we introduce\nan unsupervised video generation model that learns a prior model of uncertainty\nin a given environment. Video frames are generated by drawing samples from this\nprior and combining them with a deterministic estimate of the future frame. The\napproach is simple and easily trained end-to-end on a variety of datasets.\nSample generations are both varied and sharp, even many frames into the future,\nand compare favorably to those from existing approaches.","url_abs":"http://arxiv.org/abs/1802.07687v2","url_pdf":"http://arxiv.org/pdf/1802.07687v2.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":"stochastic-video-generation-with-a-learned","repo_url":"https://github.com/edenton/svg","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"stochastic-video-generation-with-a-learned","repo_url":"https://github.com/MIT-Omnipush/video-prediction","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"stochastic-video-generation-with-a-learned","repo_url":"https://github.com/joelouismarino/amortized-variational-filtering","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"video-generation","task_name":"Video Generation"},{"task_slug":"video-prediction","task_name":"Video Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/video-generation-on-bair-robot-pushing","task":"Video Generation","dataset":"BAIR Robot Pushing","model":"SVG (from SRVP)","rank_in_archive_order":23,"of":31,"metrics":{"Cond":"2","FVD score":"255±4","LPIPS":"0.0609±0.0034","PSNR":"18.95±0.26","Pred":"28","SSIM":"0.8058±0.0088","Train":"12"},"uses_additional_data":false},{"leaderboard":"/sota/video-generation-on-bair-robot-pushing","task":"Video Generation","dataset":"BAIR Robot Pushing","model":"SVG-LP (from vRNN)","rank_in_archive_order":24,"of":31,"metrics":{"Cond":"2","FVD score":"256.62","LPIPS":"0.061±0.03","Pred":"28","SSIM":"0.816±0.07","Train":"10"},"uses_additional_data":false},{"leaderboard":"/sota/video-generation-on-bair-robot-pushing","task":"Video Generation","dataset":"BAIR Robot Pushing","model":"SVG-FP (from FVD)","rank_in_archive_order":27,"of":31,"metrics":{"Cond":"2","FVD score":"315.5","Pred":"14","Train":"14"},"uses_additional_data":false},{"leaderboard":"/sota/video-prediction-on-cityscapes-128x128","task":"Video Prediction","dataset":"Cityscapes 128x128","model":"SVG (from Hier-VRNN)","rank_in_archive_order":3,"of":5,"metrics":{"Cond.":"2","FVD":"1300.26","LPIPS":"0.549 ± 0.06","Pred":"28","SSIM":"0.574±0.08","Train":"10"},"uses_additional_data":false},{"leaderboard":"/sota/video-prediction-on-kth","task":"Video Prediction","dataset":"KTH","model":"SVG-LP (from Grid-keypoints)","rank_in_archive_order":3,"of":31,"metrics":{"Cond":"10","FVD":"157.9","LPIPS":"0.129","PSNR":"23.91","Params (M)":"22.8","Pred":"40","SSIM":"0.800","Train":"10"},"uses_additional_data":false},{"leaderboard":"/sota/video-prediction-on-kth","task":"Video Prediction","dataset":"KTH","model":"SVG-LP (from SRVP)","rank_in_archive_order":10,"of":31,"metrics":{"Cond":"10","FVD":"377 ± 6","LPIPS":"0.0923±0.0038","PSNR":"28.06±0.29","Pred":"30","SSIM":"0.8438±0.0054","Train":"10"},"uses_additional_data":false},{"leaderboard":"/sota/video-prediction-on-synpickvp","task":"Video Prediction","dataset":"SynpickVP","model":"SVG-LP","rank_in_archive_order":4,"of":5,"metrics":{"LPIPS":"0.066","MSE":"51.82","PSNR":"27..38","SSIM":"0.886"},"uses_additional_data":false},{"leaderboard":"/sota/video-prediction-on-synpickvp","task":"Video Prediction","dataset":"SynpickVP","model":"SVG-Det","rank_in_archive_order":5,"of":5,"metrics":{"LPIPS":"0.068","MSE":"60.60","PSNR":"26.92","SSIM":"0.879"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/1802.07687","atlas_url":"https://app.syntology.ai/?focus=1802.07687","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1802.07687"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+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. 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