{"url":"/method/cspresnext","slug":"cspresnext","name":"CSPResNeXt","full_name":"CSPResNeXt","full_name_withheld":false,"description_markdown":"**CSPResNeXt** is a convolutional neural network where we apply the Cross Stage Partial Network (CSPNet) approach to [ResNeXt](https://paperswithcode.com/method/resnext). The CSPNet partitions the feature map of the base layer into two parts and then merges them through a cross-stage hierarchy. The use of a split and merge strategy allows for more gradient flow through the network.","description_state":"present","introduced_year":null,"introduced_by":{"title":"CSPNet: A New Backbone that can Enhance Learning Capability of CNN","paper":"/paper/cspnet-a-new-backbone-that-can-enhance","first_author":"Chien-Yao Wang","n_authors":6,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/cspnet-a-new-backbone-that-can-enhance"},"source":{"url":"https://arxiv.org/abs/1911.11929v1","title":"CSPNet: A New Backbone that can Enhance Learning Capability of CNN","url_on_a_paper_host":true},"code_snippet_url":"https://github.com/WongKinYiu/CrossStagePartialNetworks","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":3,"archive_num_papers":3,"papers_newest_first":[{"paper":"/paper/web-diagnosis-for-covid-19-and-pneumonia","title":"Web Diagnosis for COVID-19 and Pneumonia Based on Computed Tomography Scans and X-rays","date":"2024-01-06","arxiv_id":null,"n_code_links":2,"syntology":null},{"paper":"/paper/yolov4-optimal-speed-and-accuracy-of-object","title":"YOLOv4: Optimal Speed and Accuracy of Object Detection","date":"2020-04-23","arxiv_id":"2004.10934","n_code_links":223,"syntology":{"ran":24,"of":184,"unverified":160,"pointer_only":8}},{"paper":"/paper/cspnet-a-new-backbone-that-can-enhance","title":"CSPNet: A New Backbone that can Enhance Learning Capability of CNN","date":"2019-11-27","arxiv_id":"1911.11929","n_code_links":123,"syntology":null}],"papers_shown":3,"tasks":[{"task":"/task/object-detection","name":"Object Detection","papers":2},{"task":"/task/real-time-object-detection","name":"Real-Time Object Detection","papers":2},{"task":"/task/attribute","name":"Attribute","papers":1},{"task":"/task/machine-learning","name":"BIG-bench Machine Learning","papers":1},{"task":"/task/computed-tomography-ct","name":"Computed Tomography (CT)","papers":1},{"task":"/task/data-augmentation","name":"Data Augmentation","papers":1},{"task":"/task/image-classification","name":"Image Classification","papers":1},{"task":"/task/object","name":"Object","papers":1}],"tasks_shown":8,"n_tasks":8,"usage_by_year":[{"year":"2019","papers":1},{"year":"2020","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/cspresnext"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}