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CVPR2025-Papers-with-Code

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Project Description

CVPR 2025 论文和开源项目合集

CVPR2025-Papers-with-Code: CVPR 2025 论文和开源项目合集

Project Title

CVPR2025-Papers-with-Code — Comprehensive Repository for CVPR 2025 Papers and Open Source Projects

Overview

CVPR2025-Papers-with-Code is a curated collection of papers and open-source projects related to the Computer Vision and Pattern Recognition (CVPR) conference in 2025. This repository serves as a hub for researchers, developers, and enthusiasts to access the latest advancements in the field of computer vision, including deep learning, image processing, and related technologies.

Key Features

  • Comprehensive Coverage: Includes a wide range of topics from 3DGS to Zero-Shot Learning.
  • Open-Source Focus: Links to open-source code for practical implementation of research findings.
  • Community Engagement: Encourages community contributions through issues and discussions.

Use Cases

  • Researchers: Access the latest research papers and implementations to stay updated with the field.
  • Developers: Utilize the open-source code to integrate cutting-edge computer vision techniques into their projects.
  • Educators: Use the repository as a resource for teaching the latest trends in computer vision.

Advantages

  • Up-to-Date: Regularly updated with the latest papers and projects from CVPR 2025.
  • Organized: Categorized by topics for easy navigation and reference.
  • Community-Driven: Benefits from the collective knowledge and contributions of the computer vision community.

Limitations / Considerations

  • License Information: The license for the repository is currently unknown, which may affect the usage rights of the content.
  • Depth of Content: While the repository provides links to papers and code, the depth of explanation or tutorial material is not specified.

Similar / Related Projects

  • arXiv: A repository of electronic preprints (known as e-prints) approved for publication after moderation, but are not peer-reviewed. (Difference: arXiv is broader and not specific to CVPR.)
  • Papers with Code: A website that links state-of-the-art machine learning papers with their source code. (Difference: More general, not limited to CVPR or computer vision.)
  • GitHub Awesome Lists: Curated lists of open-source projects on GitHub. (Difference: More diverse in topics, not specific to computer vision research.)

Basic Information


📊 Project Information

🏷️ Project Topics

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Project Information

Created on 2/26/2020
Updated on 9/20/2025