{"url":"/method/flavr","slug":"flavr","name":"FLAVR","full_name":"FLAVR","full_name_withheld":false,"description_markdown":"**FLAVR** is an architecture for video frame interpolation. It uses 3D space-time convolutions to enable end-to-end learning and inference for video frame interpolation. Overall, it consists of a [U-Net](https://paperswithcode.com/method/u-net) style architecture with 3D space-time convolutions and\r\ndeconvolutions (yellow blocks). Channel gating is used after all (de-)[convolution](https://paperswithcode.com/method/convolution) layers (blue blocks). The final prediction layer (the purple block) is implemented as a convolution layer to project the 3D feature maps into $(k−1)$ frame predictions. This design allows FLAVR to predict multiple frames in one inference forward pass.","description_state":"present","introduced_year":null,"introduced_by":{"title":null,"paper":null,"first_author":null,"n_authors":0,"url_abs":null,"archive_paper_url":null},"source":{"url":"https://arxiv.org/abs/2012.08512v3","title":"FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolation","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Video Interpolation Models","url":"/methods/category/video-interpolation-models","pwc_aliases":[]}],"n_papers_tagged":2,"archive_num_papers":null,"papers_newest_first":[{"paper":null,"title":"Video Frame Interpolation for Polarization via Swin-Transformer","date":"2024-06-17","arxiv_id":"2406.11371","n_code_links":0,"syntology":null},{"paper":"/paper/flavr-flow-agnostic-video-representations-for","title":"FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolation","date":"2020-12-15","arxiv_id":"2012.08512","n_code_links":1,"syntology":null}],"papers_shown":2,"tasks":[{"task":"/task/video-frame-interpolation","name":"Video Frame Interpolation","papers":2},{"task":"/task/action-recognition-in-videos","name":"Action Recognition","papers":1},{"task":"/task/motion-magnification","name":"Motion Magnification","papers":1},{"task":"/task/optical-flow-estimation","name":"Optical Flow Estimation","papers":1}],"tasks_shown":4,"n_tasks":4,"usage_by_year":[{"year":"2020","papers":1},{"year":"2024","papers":1}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/flavr"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}