Conference Information
CVML 2025: International Conference on Computer Vision and Machine Learning
https://iccvml.com/Submission Date: |
2024-12-31 |
Notification Date: |
2025-01-10 |
Conference Date: |
2025-02-21 |
Location: |
Chengdu, China |
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Call For Papers
2025年计算机视觉与机器学习研究国际学术会议(CVML2025),由武汉大学和成都信息工程大学联合举办,将于2025年2月21-23日在四川省成都市举行。第一轮截稿日期2024年12月31日,诚邀广大师生投稿参会转发宣传!谢谢! 在CVML2025会议被录用且完成注册的论文,将由SPIE出版,并提交至EI核心以及Scopus检索。 ------------------------------------ 学术会议云:https://www.allconfs.org/meeting/index.asp?id=36418 --------------------------------------------------------------------------------------- Conference information: 1. Conference Name: 2025 International Conference on Computer Vision and Machine Learning 2. Dates: February 21-23, 2025 3. Organizer: Wuhan University 4. Indexing: EI Compendex, Scopus 5. Format: Hybrid (Virtual & In-person) 6. Website: https://iccvml.com/ --------------------------------------------------------------------------------------- INDEXING Accepted and presented papers will be submitted to El Compendex and Scopus for indexing. 收录检索:EI Compendex,Scopus【多名大咖主讲 | EI稳定检索】 --------------------------------------------------------------------------------------- FULL PAPER SUBMISSION Please refer to the Submission Guidelines for specific information and submission requirements: https://iccvml.com/?submissionguidelines/ 请选择以下投稿方式之一: CMT系统:https://cmt3.research.microsoft.com/CVML2025 电子邮件: iccvml@hotmail.com 注意:所有论文均应以英文撰写,篇幅不得少于4页。 --------------------------------------------------------------------------------------- IMPORTANT DATES - Full Paper Submission Due: December 31, 2024 - Notification of Acceptance Due: Within one week after submission - Registration Deadline: January 20, 2025 - Conference Date: February 21-23, 2025 会议日期 一轮截稿日期:2024年12月31日 录用通知日期:投稿7个工作日内 会议召开日期:2025年2月21-23日 --------------------------------------------------------------------------------------- Topic Areas This is a non-comprehensive list of topics of interest to CVML 2025. 1. Computer Vision and Imaging: - 3D from multi-view and sensors - 3D from single images - Autonomous driving - Biometrics - Computational imaging - Computer vision theory - Efficient and scalable vision - Explainable computer vision - Humans: Face, body, pose, gesture, movement - Image and video synthesis and generation - Physics-based vision and shape-from-X - Recognition: Categorization, detection, retrieval - Scene analysis and understanding - Segmentation, grouping, and shape analysis - Video: Action and event understanding 2. Machine Leaning Techniques: - Adversarial attack and defense - Deep learning architectures and techniques - Machine learning (other than deep learning) - Optimization methods (other than deep learning) - Transfer/ low-shot/ continual/ long-tail learning - Generative models - Probabilistic methods (Bayesian methods, variational inference, sampling, UQ, etc.) - Reinforcement learning - Representation learning for computer vision, audio, language, and other modalities - Metric learning, kernel learning, and sparse coding - Learning on graphs and other geometries and topologies 3. Ethics, Privacy, and Integrative Techniques: - Transparency, fairness, accountability, privacy, and ethics in vision - Vision, language, and reasoning - Self-& semi-& meta-& unsupervised learning - Robotics --------------------------------------------------------------------------------------- CONTACT Dr. Deng: iccvml@hotmail.com Ms. Li (Wechat): 17722152064
Last updated by Clara Tsai in 2024-12-17
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