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Donate arxiv logo > cs > arXiv:2401.17270 [ ] Help | Advanced Search [All fields ] Search arXiv logo Cornell University Logo [ ] GO quick links * Login * Help Pages * About Computer Science > Computer Vision and Pattern Recognition arXiv:2401.17270 (cs) [Submitted on 30 Jan 2024 (v1), last revised 22 Feb 2024 (this version, v3)] Title:YOLO-World: Real-Time Open-Vocabulary Object Detection Authors:Tianheng Cheng, Lin Song, Yixiao Ge, Wenyu Liu, Xinggang Wang , Ying Shan View a PDF of the paper titled YOLO-World: Real-Time Open-Vocabulary Object Detection, by Tianheng Cheng and 5 other authors View PDF HTML (experimental) Abstract:The You Only Look Once (YOLO) series of detectors have established themselves as efficient and practical tools. However, their reliance on predefined and trained object categories limits their applicability in open scenarios. Addressing this limitation, we introduce YOLO-World, an innovative approach that enhances YOLO with open-vocabulary detection capabilities through vision-language modeling and pre-training on large-scale datasets. Specifically, we propose a new Re-parameterizable Vision-Language Path Aggregation Network (RepVL-PAN) and region-text contrastive loss to facilitate the interaction between visual and linguistic information. Our method excels in detecting a wide range of objects in a zero-shot manner with high efficiency. On the challenging LVIS dataset, YOLO-World achieves 35.4 AP with 52.0 FPS on V100, which outperforms many state-of-the-art methods in terms of both accuracy and speed. Furthermore, the fine-tuned YOLO-World achieves remarkable performance on several downstream tasks, including object detection and open-vocabulary instance segmentation. Comments: Work still in progress. Code & models are available at: this https URL Subjects: Computer Vision and Pattern Recognition (cs.CV) Cite as: arXiv:2401.17270 [cs.CV] (or arXiv:2401.17270v3 [cs.CV] for this version) https://doi.org/10.48550/arXiv.2401.17270 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Tianheng Cheng [view email] [v1] Tue, 30 Jan 2024 18:59:38 UTC (5,276 KB) [v2] Fri, 2 Feb 2024 10:06:24 UTC (5,276 KB) [v3] Thu, 22 Feb 2024 13:05:52 UTC (5,277 KB) Full-text links: Access Paper: View a PDF of the paper titled YOLO-World: Real-Time Open-Vocabulary Object Detection, by Tianheng Cheng and 5 other authors * View PDF * HTML (experimental) * TeX Source * Other Formats license icon view license Current browse context: cs.CV < prev | next > new | recent | 2024-01 Change to browse by: cs References & Citations * NASA ADS * Google Scholar * Semantic Scholar a export BibTeX citation Loading... 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