{"url":"/method/ffmv2","slug":"ffmv2","name":"FFMv2","full_name":"Feature Fusion Module v2","full_name_withheld":false,"description_markdown":"**Feature Fusion Module v2** is a feature fusion module from the [M2Det](https://paperswithcode.com/method/m2det) object detection model, and is crucial for constructing the final multi-level feature pyramid. They use [1x1 convolution](https://paperswithcode.com/method/1x1-convolution) layers to compress the channels of the input features and use a concatenation operation to aggregate these feature map. FFMv2 takes the base feature and the largest output feature map of the previous [Thinned U-Shape Module](https://paperswithcode.com/method/tum) (TUM) – these two are of the same scale – as input, and produces the fused feature for the next TUM.","description_state":"present","introduced_year":null,"introduced_by":{"title":"M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network","paper":"/paper/m2det-a-single-shot-object-detector-based-on","first_author":"Qijie Zhao","n_authors":7,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/m2det-a-single-shot-object-detector-based-on"},"source":{"url":"http://arxiv.org/abs/1811.04533v3","title":"M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network","url_on_a_paper_host":true},"code_snippet_url":"https://github.com/qijiezhao/M2Det/blob/de4a6241bf22f7e7f46cb5cb1eb95615fd0a5e12/m2det.py#L44","code_snippet_url_on_a_code_host":true,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Feature Extractors","url":"/methods/category/feature-extractors","pwc_aliases":[]}],"n_papers_tagged":2,"archive_num_papers":2,"papers_newest_first":[{"paper":"/paper/towards-robust-visual-information-extraction","title":"Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution","date":"2021-01-24","arxiv_id":"2102.06732","n_code_links":1,"syntology":null},{"paper":"/paper/m2det-a-single-shot-object-detector-based-on","title":"M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network","date":"2018-11-12","arxiv_id":"1811.04533","n_code_links":11,"syntology":{"ran":1,"of":1,"unverified":0,"pointer_only":0}}],"papers_shown":2,"tasks":[{"task":"/task/3d-feature-matching","name":"3D Feature Matching","papers":1},{"task":"/task/decoder","name":"Decoder","papers":1},{"task":"/task/object","name":"Object","papers":1},{"task":"/task/object-detection","name":"Object Detection","papers":1},{"task":"/task/text-detection","name":"Text Detection","papers":1},{"task":"/task/text-spotting","name":"Text Spotting","papers":1},{"task":"/task/document-understanding","name":"document understanding","papers":1},{"task":"/task/object-detection-1","name":"object-detection","papers":1}],"tasks_shown":8,"n_tasks":8,"usage_by_year":[{"year":"2018","papers":1},{"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/ffmv2"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}