{"url":"/method/temporally-consistent-spatial-augmentation","slug":"temporally-consistent-spatial-augmentation","name":"Temporally Consistent Spatial Augmentation","full_name":"Temporally Consistent Spatial Augmentation","full_name_withheld":false,"description_markdown":"**Temporally Consistent Spatial Augmentation** is a video data augmentation technique used for contrastive learning in the [Contrastive Video Representation Learning](https://paperswithcode.com/method/cvrl) framework. It fixes the randomness of spatial augmentation across frames; this prevents spatial augmentation hurting learning if applied independently across frames, because in that case it breaks the natural motion. In contrast, having temporally consistent spatial augmentation does not break the natural motion in the frames.","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/2008.03800v4","title":"Spatiotemporal Contrastive Video Representation Learning","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 Data Augmentation","url":"/methods/category/video-data-augmentation","pwc_aliases":[]}],"n_papers_tagged":3,"archive_num_papers":null,"papers_newest_first":[{"paper":null,"title":"Nearest-Neighbor Inter-Intra Contrastive Learning from Unlabeled Videos","date":"2023-03-13","arxiv_id":"2303.07317","n_code_links":0,"syntology":null},{"paper":null,"title":"SCVRL: Shuffled Contrastive Video Representation Learning","date":"2022-05-24","arxiv_id":"2205.11710","n_code_links":0,"syntology":null},{"paper":"/paper/spatiotemporal-contrastive-video","title":"Spatiotemporal Contrastive Video Representation Learning","date":"2020-08-09","arxiv_id":"2008.03800","n_code_links":4,"syntology":null}],"papers_shown":3,"tasks":[{"task":"/task/contrastive-learning","name":"Contrastive Learning","papers":3},{"task":"/task/representation-learning","name":"Representation Learning","papers":2},{"task":"/task/self-supervised-learning","name":"Self-Supervised Learning","papers":2},{"task":"/task/action-recognition-in-videos","name":"Action Recognition","papers":1},{"task":"/task/data-augmentation","name":"Data Augmentation","papers":1},{"task":"/task/diversity","name":"Diversity","papers":1},{"task":"/task/self-supervised-action-recognition","name":"Self-Supervised Action Recognition","papers":1},{"task":"/task/self-supervised-action-recognition-linear","name":"Self-Supervised Action Recognition Linear","papers":1},{"task":"/task/unsupervised-pre-training","name":"Unsupervised Pre-training","papers":1}],"tasks_shown":9,"n_tasks":9,"usage_by_year":[{"year":"2020","papers":1},{"year":"2022","papers":1},{"year":"2023","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/temporally-consistent-spatial-augmentation"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}