Yonsei University’s School of Computing Has 9 Papers Accepted at CVPR 2025

Professors from Yonsei University’s School of Computing have had 9 papers accepted at the Conference on Computer Vision and Pattern Recognition (CVPR) 2025.

These papers present groundbreaking advancements in computer vision and pattern recognition, earning high praise from researchers worldwide. In particular, they introduce innovative methodologies applicable to cutting-edge fields such as deep learning-based image understanding, autonomous driving, and medical image analysis, drawing significant attention from both academia and industry.

CVPR is one of the most prestigious international conferences, where top AI and computer vision researchers gather annually to present and discuss state-of-the-art research. With its highly competitive acceptance rate, CVPR stands as a premier venue for AI research. The acceptance of these papers once again demonstrates the global research competitiveness of Yonsei University’s School of Computing and solidifies its position as a leading institution in AI research.

List of accepted papers:

1. Distilling Spectral Graph for Object-Context Aware Open-Vocabulary Semantic Segmentation

- Chanyoung Kim, Dayun Ju, Woojung Han, Ming-Hsuan Yang, Seong Jae Hwang

2. EditSplat: Multi-View Fusion and Attention-Guided Optimization for View-Consistent 3D Scene Editing with 3D Gaussian Splatting

- Dong In Lee, Hyeongcheol Park, Jiyoung Seo, Eunbyung Park, Hyunje Park, Ha Dam Baek, Shin Sangheon, Sangmin Kim, Sangpil Kim

3. Generative Densification: Learning to Densify Gaussians for High-Fidelity Generalizable 3D Reconstruction

- Seungtae Nam*, Xiangyu Sun*, Gyeongjin Kang, Younggeun Lee, Seungjun Oh, Eunbyung Park

4. Latent space Super-Resolution for Higher-Resolution Image Generation with Diffusion Models

- Jinho Jeong, Sangmin Han, Jinwoo Kim, Seon Joo Kim

5. Omni-RGPT: Unifying Image and Video Region-level Understanding via Token Marks

- Miran Heo, Min-Hung Chen, De-An Huang, Sifei Liu, Subhashree Radhakrishnan, Seon Joo Kim, Yu-Chiang Frank Wang, Ryo Hachiuma

- https://miranheo.github.io/omni-rgpt/

6. ORIDa: Object-centric Real-world Image Composition Dataset

- Jinwoo Kim, Sangmin Han, Jinho Jeong, Jiwoo Choi, Dongyoung Kim, Seon Joo Kim

7. SelfSplat: Pose-Free and 3D Prior-Free Generalizable 3D Gaussian Splatting

- Gyeongjin Kang*, Jisang Yoo*, Jihyeon Park, Seungtae Nam, Hyeonsoo Im, Sangheon Shin, Sangpil Kim, Eunbyung Park

8. Spatial Transport Optimization by Repositioning Attention Map for Training-Free Text-to-Image Synthesis

- Woojung Han, Yeonkyung Lee, Chanyoung Kim, Kwanghyun Park, Seong Jae Hwang

9. Your Large Vision-Language Model Only Needs A Few Attention Heads for Visual Grounding

- Seil Kang, Jinyoung Kim, Junhyeok Kim, Seong Jae Hwang

Image Source:CVPR Official Website (https://cvpr.thecvf.com)