{"url":"/method/twins-svt","slug":"twins-svt","name":"Twins-SVT","full_name":"Twins-SVT","full_name_withheld":false,"description_markdown":"**Twins-SVT** is a type of [vision transformer](https://paperswithcode.com/methods/category/vision-transformer) which utilizes a [spatially separable attention mechanism](https://paperswithcode.com/method/spatially-separable-self-attention) (SSAM) which is composed of two types of attention operations—(i) locally-grouped self-attention (LSA), and (ii) global sub-sampled attention (GSA), where LSA captures the fine-grained and short-distance information and GSA deals with the long-distance and global information. On top of this, it utilizes [conditional position encodings](https://paperswithcode.com/method/conditional-positional-encoding) as well as the architectural design of the [Pyramid Vision Transformer](https://paperswithcode.com/method/pvt).","description_state":"present","introduced_year":null,"introduced_by":{"title":"Twins: Revisiting the Design of Spatial Attention in Vision Transformers","paper":"/paper/twins-revisiting-spatial-attention-design-in","first_author":"Xiangxiang Chu","n_authors":8,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/twins-revisiting-spatial-attention-design-in"},"source":{"url":"https://arxiv.org/abs/2104.13840v4","title":"Twins: Revisiting the Design of Spatial Attention in Vision Transformers","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":"Vision Transformers","url":"/methods/category/vision-transformers","pwc_aliases":["vision-transformer"]}],"n_papers_tagged":1,"archive_num_papers":1,"papers_newest_first":[{"paper":"/paper/twins-revisiting-spatial-attention-design-in","title":"Twins: Revisiting the Design of Spatial Attention in Vision Transformers","date":"2021-04-28","arxiv_id":"2104.13840","n_code_links":9,"syntology":{"ran":0,"of":2,"unverified":2,"pointer_only":2}}],"papers_shown":1,"tasks":[{"task":"/task/image-classification","name":"Image Classification","papers":1},{"task":"/task/semantic-segmentation","name":"Semantic Segmentation","papers":1}],"tasks_shown":2,"n_tasks":2,"usage_by_year":[{"year":"2021","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/twins-svt"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}