CVPR征集范围

http://cvpr2020.thecvf.com/submission/main-conference/author-guidelines#call-for-papers
以上地址有提交要求和模板下载

范围

1. 3D电脑视觉 3D computer vision

2. 行动与行为识别 Action and behavior recognition

3. 对抗学习，对抗攻防方法 Adversarial learning, adversarial attack and defense methods

4. 生物特征识别，脸部，手势，身体姿势 Biometrics, face, gesture, body pose

5. 计算摄影，图像和视频合成 Computational photography, image and video synthesis

6. 数据集和评估 Datasets and evaluation

7. 网络的有效训练和推理方法 Efficient training and inference methods for networks

8. 可解释的AI，公平，问责，隐私，透明度和愿景道德 Explainable AI, fairness, accountability, privacy, transparency and ethics in vision

9. 图像检索 Image retrieval

10. 低层次的和基于物理的视觉 Low-level and physics-based vision

11. 机器学习架构和公式 Machine learning architectures and formulations

12. 医学，生物学和细胞显微镜 Medical, biological and cell microscopy

13. 运动与追踪 Motion and tracking

14. 神经生成模型，自动编码器，GAN： Neural generative models, auto encoders, GANs

15. 优化和学习方法 Optimization and learning methods

16. 识别（物体检测，分类） Recognition (object detection, categorization)

17. 表征学习，深度学习 Representation learning, deep learning

18. 场景分析与理解 Scene analysis and understanding

19. 分割，分组和形状 Segmentation, grouping and shape

20. 转移，低调，半监督和无监督学习 Transfer, low-shot, semi- and un- supervised learning

21. 视频分析与理解 Video analysis and understanding

22. 视觉+语言，视觉+其他方式 Vision + language, vision + other modalities

23. 视觉应用和系统，机器人技术和自动驾驶汽车的视觉 Vision applications and systems, vision for robotics and autonomous vehicles

24. 视觉推理和逻辑表示 Visual reasoning and logical representation

英文

3D computer vision

Action and behavior recognition

Adversarial learning, adversarial attack and defense methods

Biometrics, face, gesture, body pose

Computational photography, image and video synthesis

Datasets and evaluation

Efficient training and inference methods for networks

Explainable AI, fairness, accountability, privacy, transparency and ethics in vision

Image retrieval

Low-level and physics-based vision

Machine learning architectures and formulations

Medical, biological and cell microscopy

Motion and tracking

Neural generative models, auto encoders, GANs

Optimization and learning methods

Recognition (object detection, categorization)

Representation learning, deep learning

Scene analysis and understanding

Segmentation, grouping and shape

Transfer, low-shot, semi- and un- supervised learning

Video analysis and understanding

Vision + language, vision + other modalities

Vision applications and systems, vision for robotics and autonomous vehicles

Visual reasoning and logical representation