CVPR_Papers

<p align="left"> <a href="README_CN.md">中文</a>&nbsp;｜&nbsp;English </p> <br> # CVPR Papers <p align="center"> <img src="images/cvpr.jpeg" alt="CVPR Papers" width="900"/> </p> <p align="center"> <a href="https://github.com/choucisan/CVpaper"><img src="https://img.shields.io/badge/GitHub-CVPR_Papers-181717?style=for-the-badge&logo=github" alt="GitHub"></a> &nbsp; <a href="https://huggingface.co/datasets/choucsan/CVPR_Papers"><img src="https://img.shields.io/badge/%F0%9F%A4%97_HuggingFace-Dataset-yellow?style=for-the-badge" alt="Hugging Face"></a> &nbsp; <a href="https://modelscope.cn/datasets/choucisan/CVPR_Papers"><img src="https://img.shields.io/badge/ModelScope-Dataset-624aff?style=for-the-badge" alt="ModelScope"></a> &nbsp; <a href="https://choucisan.github.io/collections/cvpr_paper"><img src="https://img.shields.io/badge/Blog-Post-blue?style=for-the-badge" alt="Blog"></a> &nbsp; <a href="https://choosealicense.com/licenses/mit"><img src="https://img.shields.io/badge/License-MIT-green?style=for-the-badge" alt="License"></a> </p> Since 2013, deep learning has revolutionized computer vision, with CVPR (IEEE Conference on Computer Vision and Pattern Recognition) serving as the premier venue documenting this transformative journey. From AlexNet's breakthrough to the rise of Transformers, CVPR papers chronicle the complete trajectory of computer vision advancement. **CVPR Papers** is a comprehensive dataset containing all papers from CVPR 2013 to present, including metadata and PDF files. Designed for literature review, trend analysis, citation network construction, and various computer vision research tasks. --- ## Pipeline 1. **Web Scraping**: Extract paper listings from CVF Open Access repository 2. **Metadata Extraction**: Parse HTML to extract titles, authors, PDF links, and BibTeX citations 3. **Abstract Retrieval**: Fetch abstracts from individual paper detail pages 4. **PDF Download**: Concurrently download all paper PDF files 5. **Data Validation**: Verify data integrity and format consistency --- ## Dataset Structure ``` CVPR_Papers/ ├── images/ │ └── cvpr.jpeg ├── 2013/ │ ├── pdf/ # PDF files │ └── meta.jsonl # Metadata ├── 2014/ │ ├── pdf/ │ └── meta.jsonl └── ... (through 2026) ``` ## Dataset Overview - **Total Papers**: 22,521 (CVPR 2013–2026, continuously expanding) - **Data Format**: JSONL for metadata, PDF for full papers - **Source**: [CVF Open Access](https://openaccess.thecvf.com) | Field | Type | Description | |-------|------|-------------| | `title` | string | Paper title | | `authors` | string | Comma-separated list of authors | | `abstract` | string | Paper abstract | | `pdf_path` | string | Relative path to PDF file | | `download_url` | string | Direct download URL for PDF | | `bibtex` | string | BibTeX citation string | **Example:** ```json { "title": "Deformable Spatial Propagation Network for Depth Completion", "authors": "Xinjing Cheng, Peng Wang, Ruigang Yang", "abstract": "Depth completion aims to recover dense depth maps from sparse ones...", "pdf_path": "2018/pdf/Cheng_Deformable_Spatial_Propagation_CVPR_2018_paper.pdf", "bibtex": "@InProceedings{Cheng_2018_CVPR, ...}" } ``` ## Usage ```python from datasets import load_dataset dataset = load_dataset("choucsan/CVPR_Papers") # or from ModelScope from modelscope import MsDataset dataset = MsDataset.load("choucisan/CVPR_Papers") ``` ## License MIT License. ## Contact - 📧 **[e-mail]** - 🤗 [Hugging Face](https://huggingface.co/datasets/choucsan/CVPR_Papers) - 🐱 [ModelScope](https://modelscope.cn/datasets/choucisan/CVPR_Papers)