{"url":"/method/tridentnet","slug":"tridentnet","name":"TridentNet","full_name":"TridentNet","full_name_withheld":false,"description_markdown":"**TridentNet** is an object detection architecture that aims to generate scale-specific feature\r\nmaps with a uniform representational power.  A parallel multi-branch architecture is constructed in which each branch shares the same transformation parameters but with different receptive fields. A scale-aware training scheme is used to specialize each branch by sampling object instances of proper scales for training.","description_state":"present","introduced_year":null,"introduced_by":{"title":"Scale-Aware Trident Networks for Object Detection","paper":"/paper/scale-aware-trident-networks-for-object","first_author":"Yanghao Li","n_authors":4,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/scale-aware-trident-networks-for-object"},"source":{"url":"https://arxiv.org/abs/1901.01892v2","title":"Scale-Aware Trident Networks for Object Detection","url_on_a_paper_host":true},"code_snippet_url":"https://github.com/facebookresearch/detectron2/tree/master/projects/TridentNet/","code_snippet_url_on_a_code_host":true,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Object Detection Models","url":"/methods/category/object-detection-models","pwc_aliases":[]}],"n_papers_tagged":3,"archive_num_papers":3,"papers_newest_first":[{"paper":"/paper/deep-learning-approaches-to-building-rooftop","title":"Deep learning approaches to building rooftop thermal bridge detection from aerial images","date":"2022-12-12","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"title":"DRPN: Making CNN Dynamically Handle Scale Variation","date":"2021-12-21","arxiv_id":"2112.10963","n_code_links":0,"syntology":null},{"paper":"/paper/scale-aware-trident-networks-for-object","title":"Scale-Aware Trident Networks for Object Detection","date":"2019-01-07","arxiv_id":"1901.01892","n_code_links":4,"syntology":null}],"papers_shown":3,"tasks":[{"task":"/task/object-detection","name":"Object Detection","papers":2},{"task":"/task/instance-segmentation","name":"Instance Segmentation","papers":1},{"task":"/task/object","name":"Object","papers":1},{"task":"/task/object-detection-1","name":"object-detection","papers":1}],"tasks_shown":4,"n_tasks":4,"usage_by_year":[{"year":"2019","papers":1},{"year":"2021","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/tridentnet"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}