8 citations · 41 across the 34 of their papers we have counts for
8 papers · 1 filter
Elevating Flow-Guided Video Inpainting with Reference Generation
Suhwan Cho, Seoung Wug Oh, Sangyoun Lee +1
Video inpainting (VI) is a challenging task that requires effective propagation of observable content across frames while simultaneously generating new content not present in the o…
CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images
Jungho Lee, Suhwan Cho, Taeoh Kim +6
3D Gaussian Splatting (3DGS) has attracted significant attention for its high-quality novel view rendering, inspiring research to address real-world challenges. While conventional…
STATIC : Surface Temporal Affine for TIme Consistency in Video Monocular Depth Estimation
Sunghun Yang, Minhyeok Lee, Suhwan Cho +2
Video monocular depth estimation is essential for applications such as autonomous driving, AR/VR, and robotics. Recent transformer-based single-image monocular depth estimation mod…
Transforming Static Images Using Generative Models for Video Salient Object Detection
Suhwan Cho, Minhyeok Lee, Jungho Lee +1
In many video processing tasks, leveraging large-scale image datasets is a common strategy, as image data is more abundant and facilitates comprehensive knowledge transfer. A typic…
Effective SAM Combination for Open-Vocabulary Semantic Segmentation
Minhyeok Lee, Suhwan Cho, Jungho Lee +4
Open-vocabulary semantic segmentation aims to assign pixel-level labels to images across an unlimited range of classes. Traditional methods address this by sequentially connecting…
Video Diffusion Models are Strong Video Inpainter
Minhyeok Lee, Suhwan Cho, Chajin Shin +3
Propagation-based video inpainting using optical flow at the pixel or feature level has recently garnered significant attention. However, it has limitations such as the inaccuracy…