Most Influential ICCV Papers (2025-09 Version)
Summary
Paper Digest has released its "Most Influential ICCV Papers (2025-09 Version)" list, identifying the top 15 papers from each International Conference on Computer Vision (ICCV) year, spanning from 1988 to 2023. This ranking is dynamically generated based on citations from both research papers and granted patents, ensuring it reflects current impact. The 2023 list features prominent works like "Segment Anything" and "Adding Conditional Control to Text-to-Image Diffusion Models," both with an influence factor (IF) of 8. Earlier influential papers include "Mask R-CNN" (2017, IF:10) and "Swin Transformer" (2021, IF:9). The platform also offers services for searching, reviewing, and browsing productive authors by year, and provides AI-powered tools for research tasks.
Key takeaway
For Computer Vision Engineers seeking foundational or cutting-edge research, you should consult the Paper Digest's ICCV influential papers list to identify high-impact works. Focus on papers with strong citation metrics, particularly those also cited in patents, as these often indicate practical relevance and long-term significance. Use the platform's tools to quickly navigate the extensive research landscape and inform your project decisions.
Key insights
Citation analysis of ICCV papers reveals enduring influence across computer vision research and patent landscapes.
Principles
- Influence extends beyond initial publication to patent citations.
- New methodologies often combine existing techniques for novel applications.
- Large datasets are crucial for advancing deep learning models.
Method
Paper Digest automatically ranks papers by aggregating citations from research publications and granted patents, with frequent updates to reflect evolving influence.
In practice
- Explore top-cited papers for foundational methods in computer vision.
- Utilize Paper Digest's search tools for specific ICCV topics.
- Investigate papers with high 'IF' scores for impactful research.
Topics
- Diffusion Models
- Vision Transformers
- Image Segmentation
- 3D Computer Vision
- Object Detection
Best for: Computer Vision Engineer, AI Researcher, AI Scientist, Research Scientist
Related on AIssential
Editorial summary, takeaway, and curation by AIssential. Original article published by Computer Vision – Resources | Paper Digest.