The horizon line is an important contextual attribute for a wide variety of image understanding tasks. As such, many methods have been proposed to estimate its location from a single image. These methods typically require the image to contain specific cues, such as vanishing points, coplanar circles, and regular textures, thus limiting their real-world applicability. We introduce a large, realistic evaluation dataset, Horizon Lines in the Wild (HLW), containing natural images with labeled horizon lines. Using this dataset, we investigate the application of convolutional neural networks for directly estimating the horizon line, without requiring any explicit geometric constraints or other special cues. An extensive evaluation shows that using our CNNs, either in isolation or in conjunction with a previous geometric approach, we achieve state-of-the-art results on the challenging HLW dataset and two existing benchmark datasets.
Wildfire Smoke Detection System: Model Architecture, Training Mechanism, and Dataset
State Key Laboratory of Fire Science, University of Science and Technology of China（火灾科学国家重点实验室，中国科学技术大学）；Institute of Advanced Technology, University of Science and Technology of China（先进科技研究院，中国科学技术大学）；iFIRE TEK Co., Ltd.（iFIRE TEK公司）
RescueBench: Can Embodied Agents Save Lives in the Wild ?
Beihang University（北京航空航天大学）；Beijing Normal University（北京师范大学）；Peking University（北京大学）；City University of Macau（澳门城市大学）；ATEC2025 Challenge Committee（ATEC2025挑战委员会）
SenseTime Research and Tetras.AI（商汤科技研究院与Tetras.AI）；Rutgers University（罗格斯大学）；Sun Yat-sen University（中山大学）；Shanghai AI Laboratory（上海人工智能实验室）；S-Lab Nanyang Technological University（南洋理工大学S-Lab）
A Robust Attentional Framework for License Plate Recognition in the Wild
Northwestern Polytechnical University（西北工业大学）；National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology（空天地海一体化大数据应用技术国家工程实验室）；The University of Adelaide（阿德莱德大学）；Minsheng Fintech Corp. LTD（民生金融科技有限公司）
Jet Propulsion Laboratory（喷气推进实验室）；California Institute of Technology（加州理工学院）；Swiss Federal Institute of Technology（瑞士联邦理工学院）；ETH Zürich（苏黎世联邦理工学院）；FieldAI Inc.（FieldAI公司）；Stanford University（斯坦福大学）；University of California Berkeley（加州大学伯克利分校）
