{"url":"/method/sifa","slug":"sifa","name":"SIFA","full_name":"Synergistic Image and Feature Alignment","full_name_withheld":false,"description_markdown":"**Synergistic Image and Feature Alignment** is an unsupervised domain adaptation framework that conducts synergistic alignment of domains from both image and feature perspectives. In SIFA, we simultaneously transform the appearance of images across domains and enhance domain-invariance of the extracted features by leveraging adversarial learning in multiple aspects and with a deeply supervised mechanism. The feature encoder is shared between both adaptive perspectives to leverage their mutual benefits via end-to-end learning.","description_state":"present","introduced_year":null,"introduced_by":{"title":"Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation","paper":"/paper/unsupervised-bidirectional-cross-modality","first_author":"Cheng Chen","n_authors":5,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/unsupervised-bidirectional-cross-modality"},"source":{"url":"https://arxiv.org/abs/2002.02255v1","title":"Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"General","area_id":"general","collection":"Domain Adaptation","url":"/methods/category/domain-adaptation","pwc_aliases":[]}],"n_papers_tagged":2,"archive_num_papers":2,"papers_newest_first":[{"paper":"/paper/stand-alone-inter-frame-attention-in-video-1","title":"Stand-Alone Inter-Frame Attention in Video Models","date":"2022-06-14","arxiv_id":"2206.06931","n_code_links":1,"syntology":null},{"paper":"/paper/unsupervised-bidirectional-cross-modality","title":"Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation","date":"2020-02-06","arxiv_id":"2002.02255","n_code_links":1,"syntology":null}],"papers_shown":2,"tasks":[{"task":"/task/action-classification","name":"Action Classification","papers":1},{"task":"/task/action-recognition-in-videos","name":"Action Recognition","papers":1},{"task":"/task/domain-adaptation","name":"Domain Adaptation","papers":1},{"task":"/task/image-segmentation","name":"Image Segmentation","papers":1},{"task":"/task/medical-image-segmentation","name":"Medical Image Segmentation","papers":1},{"task":"/task/organ-segmentation","name":"Organ Segmentation","papers":1},{"task":"/task/segmentation","name":"Segmentation","papers":1},{"task":"/task/semantic-segmentation","name":"Semantic Segmentation","papers":1},{"task":"/task/unsupervised-domain-adaptation","name":"Unsupervised Domain Adaptation","papers":1},{"task":"/task/video-understanding","name":"Video Understanding","papers":1}],"tasks_shown":10,"n_tasks":10,"usage_by_year":[{"year":"2020","papers":1},{"year":"2022","papers":1}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/sifa"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}