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。
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学术会议云:https://www.allconfs.org/meeting/index.asp?id=36418

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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/

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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】

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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。

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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
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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

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CONTACT

Dr. Deng: iccvml@hotmail.com
Ms. Li (Wechat): 17722152064
Last updated by Clara Tsai in 2024-12-17
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