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CV Paper Portal: One-Stop Retrieval Platform for Top Conference Papers in Computer Vision

This article introduces the CV Paper Portal project, an open-source paper retrieval platform maintained by Dr. Hongsong Wang. The project integrates paper data from top computer vision and machine learning conferences such as CVPR, ICCV, ECCV, NeurIPS, and ICML, and provides keyword-based retrieval functionality, greatly facilitating literature research for researchers and students.

计算机视觉论文检索CVPRICCVNeurIPSICML学术资源文献调研ArXiv开源项目
Published 2026-05-05 11:10Recent activity 2026-05-05 11:24Estimated read 6 min
CV Paper Portal: One-Stop Retrieval Platform for Top Conference Papers in Computer Vision
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Section 01

[Introduction] CV Paper Portal: One-Stop Retrieval Platform for Top Conference Papers in Computer Vision

This article introduces the CV Paper Portal, an open-source project maintained by Dr. Hongsong Wang. The platform integrates paper data from top computer vision and machine learning conferences including CVPR, ICCV, ECCV, NeurIPS, and ICML, and provides functions like keyword retrieval, greatly facilitating literature research for researchers and students.

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Section 02

Project Background: Solving the Problem of Retrieving Top Conference Papers

In the fields of artificial intelligence and computer vision, top conferences like CVPR and ICCV accept thousands of papers each year. Researchers and students face challenges in efficiently retrieving and tracking research results. CV Paper Portal aims to build a unified retrieval platform by integrating data from multiple top conferences to improve the efficiency of literature research.

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Section 03

Core Features: Comprehensive Coverage and Convenient Retrieval

Comprehensive Conference Coverage

Covers paper data from computer vision, machine learning, multimedia graphics, and comprehensive AI conferences such as CVPR (2013-2026), ICCV (2013-2025), ECCV (2018-2024), with a time span from 2009 to 2026.

Convenient Retrieval Methods

Provides functions such as the ArXiv paper search portal (http://47.102.131.153/), year-based browsing, and keyword retrieval.

Timely Data Updates

2026 updates include the launch of the ArXiv portal, update of the CVPR 2026 page, and addition of AAAI 2026 paper links.

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Section 04

Technical Implementation: Data Sources and Architecture

Data Collection

Most paper abstracts are collected from ArXiv (https://arxiv.org/), as many top conference papers are uploaded to ArXiv before formal publication.

Website Architecture

Uses GitHub Pages to host static web pages, with advantages including free hosting, fast access, version control, and community collaboration.

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Section 05

Usage Value and Community Recognition

Usage Scenarios

  • Literature research: quickly retrieve relevant keywords to build literature reviews;
  • Track cutting-edge developments: view the latest conference papers to understand field progress;
  • Teaching assistance: help teachers find classic and latest achievements;
  • Cross-domain research: discover connections between methodologies in different fields.

Community Recognition

  • Featured in the official WeChat public account of the Chinese Society of Image and Graphics (CSIG);
  • Serves researchers, students, and engineers in the global CV and ML fields;
  • Open-source code provides a reference template for other projects.
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Section 06

Related Projects: Building an Academic Resource Network

CV Paper Portal is part of the author's academic resource network, with related projects including:

  • AI_arXiv_Portal: Focuses on ArXiv paper retrieval in the AI field;
  • CS_arXiv_Paper: Covers a wider range of computer science fields;
  • BestPaperAwards_AI: Collects best paper awards in the AI field.
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Section 08

Summary and Outlook

CV Paper Portal is an academic public welfare project that creates value for the community through data organization and open sharing. Future expansions may include:

  • More professional conferences in sub-fields;
  • More powerful retrieval and recommendation functions;
  • Integration with academic social networks;
  • Visualization of paper impact indicators.

This platform is a valuable resource worth bookmarking for CV and AI researchers.