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In this work, we propose a\nvideo frame interpolation method which explicitly detects the occlusion by\nexploring the depth information. Specifically, we develop a depth-aware flow\nprojection layer to synthesize intermediate flows that preferably sample closer\nobjects than farther ones. In addition, we learn hierarchical features to\ngather contextual information from neighboring pixels. The proposed model then\nwarps the input frames, depth maps, and contextual features based on the\noptical flow and local interpolation kernels for synthesizing the output frame.\nOur model is compact, efficient, and fully differentiable. Quantitative and\nqualitative results demonstrate that the proposed model performs favorably\nagainst state-of-the-art frame interpolation methods on a wide variety of\ndatasets.","url_abs":"http://arxiv.org/abs/1904.00830v1","url_pdf":"http://arxiv.org/pdf/1904.00830v1.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":"depth-aware-video-frame-interpolation","repo_url":"https://github.com/baowenbo/DAIN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"depth-aware-video-frame-interpolation","repo_url":"https://github.com/jcao216/DAIN_Modified","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"depth-aware-video-frame-interpolation","repo_url":"https://github.com/nihui/dain-ncnn-vulkan","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"depth-aware-video-frame-interpolation","repo_url":"https://github.com/BurguerJohn/Dain-App","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"depth-aware-video-frame-interpolation","repo_url":"https://github.com/MohamedAliRashad/Crystal","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"optical-flow-estimation","task_name":"Optical Flow Estimation"},{"task_slug":"video-frame-interpolation","task_name":"Video Frame Interpolation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/video-frame-interpolation-on-middlebury","task":"Video Frame Interpolation","dataset":"Middlebury","model":"DAIN","rank_in_archive_order":5,"of":11,"metrics":{"Interpolation Error":"4.86"},"uses_additional_data":false},{"leaderboard":"/sota/video-frame-interpolation-on-ucf101-1","task":"Video Frame Interpolation","dataset":"UCF101","model":"DAIN","rank_in_archive_order":16,"of":19,"metrics":{"PSNR":"34.99","SSIM":"0.9683"},"uses_additional_data":false},{"leaderboard":"/sota/video-frame-interpolation-on-vimeo90k","task":"Video Frame Interpolation","dataset":"Vimeo90K","model":"DAIN","rank_in_archive_order":18,"of":23,"metrics":{"PSNR":"34.71","SSIM":"0.9756"},"uses_additional_data":false},{"leaderboard":"/sota/video-frame-interpolation-on-vimeo90k","task":"Video Frame Interpolation","dataset":"Vimeo90K","model":"DAIN","rank_in_archive_order":19,"of":23,"metrics":{"PSNR":"34.71"},"uses_additional_data":false},{"leaderboard":"/sota/video-frame-interpolation-on-x4k1000fps","task":"Video Frame Interpolation","dataset":"X4K1000FPS","model":"DAIN_f","rank_in_archive_order":15,"of":20,"metrics":{"PSNR":"27.52","SSIM":"0.821","tOF":"3.47"},"uses_additional_data":false},{"leaderboard":"/sota/video-frame-interpolation-on-x4k1000fps","task":"Video Frame Interpolation","dataset":"X4K1000FPS","model":"DAIN","rank_in_archive_order":16,"of":20,"metrics":{"PSNR":"26.78","SSIM":"0.807","tOF":"3.83"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1904.00830","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.00830"}},"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. 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