ICCV_Papers

<p align="left"> <a href="README_CN.md">中文</a>&nbsp;｜&nbsp;English </p> <br> # ICCV Papers <p align="center"> <img src="images/iccv.jpeg" alt="ICCV Papers" width="900"/> </p> <p align="center"> <a href="https://github.com/choucisan/CVpaper"><img src="https://img.shields.io/badge/GitHub-ICCV_Papers-181717?style=for-the-badge&logo=github" alt="GitHub"></a> &nbsp; <a href="https://huggingface.co/datasets/choucsan/ICCV_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/ICCV_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/iccv_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> ICCV (International Conference on Computer Vision) is one of the most prestigious conferences in computer vision, held biennially since 1987. Along with CVPR and ECCV, it forms the top-tier venues for computer vision research. ICCV papers have contributed groundbreaking work in object detection, image segmentation, 3D reconstruction, and video understanding. **ICCV Papers** is a comprehensive dataset containing all papers from ICCV 2013 to present, including metadata and PDF download links. 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. **URL Generation**: Generate direct download URLs for PDFs 5. **Data Validation**: Verify data integrity and format consistency --- ## Dataset Structure ``` ICCV_Papers/ ├── images/ │ └── iccv.jpeg ├── 2013/ │ ├── pdf/ # PDF files │ └── meta.jsonl # Metadata ├── 2015/ │ ├── pdf/ │ └── meta.jsonl └── ... (through 2025) ``` ## Dataset Overview - **Total Papers**: 9,145 (ICCV 2013–2025, 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 | ## Usage ```python from datasets import load_dataset dataset = load_dataset("choucsan/ICCV_Papers") # or from ModelScope from modelscope import MsDataset dataset = MsDataset.load("choucisan/ICCV_Papers") ``` ## License MIT License. ## Contact - 📧 **[e-mail]** - 🤗 [Hugging Face](https://huggingface.co/datasets/choucsan/ICCV_Papers) - 🐱 [ModelScope](https://modelscope.cn/datasets/choucisan/ICCV_Papers)