{"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/places205-vggnet-models-for-scene-recognition","title":"Places205-VGGNet Models for Scene Recognition","arxiv_id":"1508.01667","date":"2015-08-07","proceeding":null,"authors":["Limin Wang","Sheng Guo","Weilin Huang","Yu Qiao"],"abstract":"VGGNets have turned out to be effective for object recognition in still\nimages. However, it is unable to yield good performance by directly adapting\nthe VGGNet models trained on the ImageNet dataset for scene recognition. This\nreport describes our implementation of training the VGGNets on the large-scale\nPlaces205 dataset. Specifically, we train three VGGNet models, namely\nVGGNet-11, VGGNet-13, and VGGNet-16, by using a Multi-GPU extension of Caffe\ntoolbox with high computational efficiency. We verify the performance of\ntrained Places205-VGGNet models on three datasets: MIT67, SUN397, and\nPlaces205. Our trained models achieve the state-of-the-art performance on these\ndatasets and are made public available.","url_abs":"http://arxiv.org/abs/1508.01667v1","url_pdf":"http://arxiv.org/pdf/1508.01667v1.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":"places205-vggnet-models-for-scene-recognition","repo_url":"https://github.com/wanglimin/Places205-VGGNet","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"places205-vggnet-models-for-scene-recognition","repo_url":"https://github.com/MS-Mind/MS-Code-02/tree/main/configs/vgg","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null}],"tasks":[{"task_slug":"computational-efficiency","task_name":"Computational Efficiency"},{"task_slug":null,"task_name":"GPU"},{"task_slug":"object-recognition","task_name":"Object Recognition"},{"task_slug":"scene-recognition","task_name":"Scene Recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1508.01667","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}