# CVML 2025 : 2025 International Conference on Computer Vision and Machine Learning

Conference completed its latest edition on February 21, 2025 in China. Primary subject areas for this edition include Robotics & Autonomous Systems, Artificial Intelligence and Uncategorized.

**Type**: Conference
**Status**: Expired
**Verified On**: 9th May, 2026

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## ⏱ Critical Deadline
> *No submission deadline specified*

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## 📍 Event Information
- **Mode**: In Person
- **Location**: China
- **Field**: Interdisciplinary
- **Date**: February 21-23, 2025
- **Official Website**: [https://iccvml.com/](https://iccvml.com/?utm_source=callforpaper.org)

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## 📝 Call for Papers Description

<p><a href="https://callforpaper.org/categories/conomie" title="Browse  call for papers" rel="follow" aria-label="View more  call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors"></a>Topic Areas
<br>This is a non-comprehensive list of topics of interest to CVML 2025.<br />
<br>
<br>1. <a href="https://callforpaper.org/categories/computer-vision" title="Browse Computer Vision call for papers" rel="follow" aria-label="View more Computer Vision call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">Computer Vision</a> and Imaging:
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<br>- 3D from multi-view and sensors
<br>- 3D from single images
<br>- Autonomous driving
<br>- <a href="https://callforpaper.org/categories/biometrics-1" title="Browse Biometrics call for papers" rel="follow" aria-label="View more Biometrics call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">Biometrics</a>
<br>- Computational imaging
<br>- Computer vision <a href="https://callforpaper.org/categories/theory-1" title="Browse theory call for papers" rel="follow" aria-label="View more theory call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">theory</a>
<br>- Efficient and scalable vision
<br>- Explainable computer vision
<br>- Humans: Face, body, pose, gesture, movement
<br>- Image and video synthesis and generation
<br>- <a href="https://callforpaper.org/categories/physics-1" title="Browse Physics call for papers" rel="follow" aria-label="View more Physics call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">Physics</a>-based vision and shape-from-X
<br>- Recognition: Categorization, detection, retrieval
<br>- Scene analysis and understanding
<br>- Segmentation, grouping, and shape analysis
<br>- Video: Action and event understanding
<br>
<br>2. Machine Leaning Techniques:
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<br>- Adversarial attack and defense
<br>- <a href="https://callforpaper.org/categories/deep-learning-2" title="Browse Deep learning call for papers" rel="follow" aria-label="View more Deep learning call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">Deep learning</a> architectures and techniques
<br>- <a href="https://callforpaper.org/categories/machine-learning-3" title="Browse Machine learning call for papers" rel="follow" aria-label="View more Machine learning call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">Machine learning</a> (other than deep learning)
<br>- <a href="https://callforpaper.org/categories/optimization-1" title="Browse Optimization call for papers" rel="follow" aria-label="View more Optimization call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">Optimization</a> methods (other than deep learning)
<br>- Transfer/ low-shot/ continual/ long-tail learning
<br>- Generative <a href="https://callforpaper.org/categories/models" title="Browse models call for papers" rel="follow" aria-label="View more models call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">models</a>
<br>- Probabilistic methods (Bayesian methods, variational inference, sampling, UQ, etc.)
<br>- Reinforcement learning
<br>- Representation learning for computer vision, <a href="https://callforpaper.org/categories/audio-1" title="Browse audio call for papers" rel="follow" aria-label="View more audio call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">audio</a>, language,  and other modalities
<br>- Metric learning, kernel learning, and sparse coding
<br>- Learning on graphs and other geometries and topologies
<br>
<br>
<br>3. <a href="https://callforpaper.org/categories/ethics-1" title="Browse Ethics call for papers" rel="follow" aria-label="View more Ethics call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">Ethics</a>, Privacy, and Integrative Techniques:
<br>
<br>- Transparency, fairness, accountability, privacy, and ethics in vision
<br>- Vision, language, and reasoning
<br>- Self-&amp; semi-&amp; meta-&amp; unsupervised learning
<br>- <a href="https://callforpaper.org/categories/robotics-3" title="Browse Robotics call for papers" rel="follow" aria-label="View more Robotics call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">Robotics</a>
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<br>IMPORTANT DATES
<br>
<br>- Full Paper Submission Due: December 31, 2024
<br>- Notification of Acceptance Due: Within one week after submission
<br>- Registration Deadline: January 20, 2025
<br>- <a href="https://callforpaper.org/categories/conference-1" title="Browse Conference call for papers" rel="follow" aria-label="View more Conference call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">Conference</a> Date: February 21-23, 2025
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<br>
<br>FULL PAPER SUBMISSION
<br>
<br>If you wish to have your paper published in the conference proceedings, please submit the full paper through the CMT system (the link above):
<br>
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<br>
<br>CONTACT
<br>
<br>Dr. Deng: <a href="mailto:iccvml@hotmail.com">iccvml@hotmail.com</a>
<br>Ms. Li (Wechat): 17722152064
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## 🏷 Taxonomy &amp; Topics
- **Primary Category**: N/A
- **Research Fields**: 
  - Robotics &amp; Autonomous Systems
  - Artificial Intelligence
  - Uncategorized

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## 🧭 Agent Instructions
- **Standard Link**: `https://callforpaper.org/call-for-papers-cvml-2025-2025-international-conference-on-computer-vision-and-machine-learning`
- **Markdown Link**: `https://callforpaper.org/call-for-papers-cvml-2025-2025-international-conference-on-computer-vision-and-machine-learning.md`
- **PDF Version**: `https://callforpaper.org/cfp/call-for-papers-cvml-2025-2025-international-conference-on-computer-vision-and-machine-learning.pdf`



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## 🎓 Academic Citations &amp; Bibliographic Records

Use these pre-formatted snippets to cite this Call for Papers in publications or reference managers:

### Plain Text
```text
CVML 2025 : 2025 International Conference on Computer Vision and Machine Learning. China, February 21–23, 2025. Available at: https://callforpaper.org/call-for-papers-cvml-2025-2025-international-conference-on-computer-vision-and-machine-learning. Accessed: July 25, 2026.
```

### APA Style 7th edition
```text
CVML 2025 : 2025 International Conference on Computer Vision and Machine Learning. (2025, February 21–23). China. https://callforpaper.org/call-for-papers-cvml-2025-2025-international-conference-on-computer-vision-and-machine-learning
```

### IEEE
```text
&quot;CVML 2025 : 2025 International Conference on Computer Vision and Machine Learning,&quot; China, Feb. 21–23, 2025. [Online]. Available: https://callforpaper.org/call-for-papers-cvml-2025-2025-international-conference-on-computer-vision-and-machine-learning. [Accessed: July 25, 2026].
```

### BibTeX
```bibtex
@misc{cvml20252025cfp,
  title     = {CVML 2025 : 2025 International Conference on Computer Vision and Machine Learning},
  year      = {2025},
  month     = feb,
  address   = {China},
  url       = {https://callforpaper.org/call-for-papers-cvml-2025-2025-international-conference-on-computer-vision-and-machine-learning},
  note      = {Call for Papers. Accessed: 2026-07-25}
}
```

### RIS (Reference Manager, EndNote)
```ris
TY  - CONF
TI  - CVML 2025 : 2025 International Conference on Computer Vision and Machine Learning
PY  - 2025
DA  - 2025/02/21
CY  - China
UR  - https://callforpaper.org/call-for-papers-cvml-2025-2025-international-conference-on-computer-vision-and-machine-learning
N1  - Call for Papers. Accessed: 2026-07-25
ER  -
```