{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/resnet-in-resnet-generalizing-residual","title":"Resnet in Resnet: Generalizing Residual Architectures","arxiv_id":"1603.08029","date":"2016-03-25","proceeding":null,"authors":["Sasha Targ","Diogo Almeida","Kevin Lyman"],"abstract":"Residual networks (ResNets) have recently achieved state-of-the-art on\nchallenging computer vision tasks. We introduce Resnet in Resnet (RiR): a deep\ndual-stream architecture that generalizes ResNets and standard CNNs and is\neasily implemented with no computational overhead. RiR consistently improves\nperformance over ResNets, outperforms architectures with similar amounts of\naugmentation on CIFAR-10, and establishes a new state-of-the-art on CIFAR-100.","url_abs":"http://arxiv.org/abs/1603.08029v1","url_pdf":"http://arxiv.org/pdf/1603.08029v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"resnet-in-resnet-generalizing-residual","repo_url":"https://github.com/osmr/imgclsmob","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"mxnet","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[],"methods":[{"method_slug":"1x1-convolution","method_name":"1x1 Convolution"},{"method_slug":"average-pooling","method_name":"Average Pooling"},{"method_slug":"batch-normalization","method_name":"Batch Normalization"},{"method_slug":"bottleneck-residual-block","method_name":"Bottleneck Residual Block"},{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"global-average-pooling","method_name":"Global Average Pooling"},{"method_slug":"kaiming-initialization","method_name":"Kaiming Initialization"},{"method_slug":"max-pooling","method_name":"Max Pooling"},{"method_slug":"relu","method_name":"ReLU"},{"method_slug":"residual-block","method_name":"Residual Block"},{"method_slug":"residual-connection","method_name":"Residual Connection"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1603.08029","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}