{"url":"/method/multigrain","slug":"multigrain","name":"MultiGrain","full_name":"MultiGrain","full_name_withheld":false,"description_markdown":"**MultiGrain** is a type of image model that learns a single embedding for classes, instances and copies.  In other words, it is a convolutional neural network that is suitable for both image classification and instance retrieval. We learn MultiGrain by jointly training an image embedding for multiple tasks. The resulting representation is compact and can outperform narrowly-trained embeddings. The learned embedding output incorporates different levels of granularity.","description_state":"present","introduced_year":null,"introduced_by":{"title":"MultiGrain: a unified image embedding for classes and instances","paper":"/paper/multigrain-a-unified-image-embedding-for","first_author":"Maxim Berman","n_authors":5,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/multigrain-a-unified-image-embedding-for"},"source":{"url":"http://arxiv.org/abs/1902.05509v2","title":"MultiGrain: a unified image embedding for classes and instances","url_on_a_paper_host":true},"code_snippet_url":"https://github.com/facebookresearch/multigrain/blob/172bb2a2ef8a7f69f02fd6a4eb20c9c3d5d7a909/multigrain/lib/multigrain.py#L24","code_snippet_url_on_a_code_host":true,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Convolutional Neural Networks","url":"/methods/category/convolutional-neural-networks","pwc_aliases":[]}],"n_papers_tagged":2,"archive_num_papers":2,"papers_newest_first":[{"paper":"/paper/efficient-probabilistic-modeling-of","title":"Efficient Probabilistic Modeling of Crystallization at Mesoscopic Scale","date":"2024-05-26","arxiv_id":"2405.16608","n_code_links":1,"syntology":{"ran":10,"of":17,"unverified":7,"pointer_only":0}},{"paper":"/paper/multigrain-a-unified-image-embedding-for","title":"MultiGrain: a unified image embedding for classes and instances","date":"2019-02-14","arxiv_id":"1902.05509","n_code_links":3,"syntology":{"ran":1,"of":4,"unverified":3,"pointer_only":0}}],"papers_shown":2,"tasks":[{"task":"/task/classification-1","name":"Classification","papers":1},{"task":"/task/data-augmentation","name":"Data Augmentation","papers":1},{"task":"/task/classification","name":"General Classification","papers":1},{"task":"/task/image-classification","name":"Image Classification","papers":1},{"task":"/task/image-retrieval","name":"Image Retrieval","papers":1},{"task":"/task/object","name":"Object","papers":1},{"task":"/task/physical-simulations","name":"Physical Simulations","papers":1},{"task":"/task/retrieval","name":"Retrieval","papers":1},{"task":"/task/image-classification","name":"image-classification","papers":1}],"tasks_shown":9,"n_tasks":9,"usage_by_year":[{"year":"2019","papers":1},{"year":"2024","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/multigrain"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}