{"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/lcnn-low-level-feature-embedded-cnn-for","title":"LCNN: Low-level Feature Embedded CNN for Salient Object Detection","arxiv_id":"1508.03928","date":"2015-08-17","proceeding":null,"authors":["Hongyang Li","Huchuan Lu","Zhe Lin","Xiaohui Shen","Brian Price"],"abstract":"In this paper, we propose a novel deep neural network framework embedded with\nlow-level features (LCNN) for salient object detection in complex images. We\nutilise the advantage of convolutional neural networks to automatically learn\nthe high-level features that capture the structured information and semantic\ncontext in the image. In order to better adapt a CNN model into the saliency\ntask, we redesign the network architecture based on the small-scale datasets.\nSeveral low-level features are extracted, which can effectively capture\ncontrast and spatial information in the salient regions, and incorporated to\ncompensate with the learned high-level features at the output of the last fully\nconnected layer. The concatenated feature vector is further fed into a\nhinge-loss SVM detector in a joint discriminative learning manner and the final\nsaliency score of each region within the bounding box is obtained by the linear\ncombination of the detector's weights. Experiments on three challenging\nbenchmark (MSRA-5000, PASCAL-S, ECCSD) demonstrate our algorithm to be\neffective and superior than most low-level oriented state-of-the-arts in terms\nof P-R curves, F-measure and mean absolute errors.","url_abs":"http://arxiv.org/abs/1508.03928v1","url_pdf":"http://arxiv.org/pdf/1508.03928v1.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":"lcnn-low-level-feature-embedded-cnn-for","repo_url":"https://github.com/MindCode-4/code-12/tree/main/lcn-master-ms","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null}],"tasks":[{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"salient-object-detection","task_name":"RGB Salient Object Detection"},{"task_slug":"salient-object-detection-1","task_name":"Salient Object Detection"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[{"method_slug":"svm","method_name":"SVM"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}