5 papers · 1 filter
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…
CRiM-GS: Continuous Rigid Motion-Aware Gaussian Splatting from Motion-Blurred Images
Jungho Lee, Donghyeong Kim, Dogyoon Lee +3
3D Gaussian Splatting (3DGS) has gained significant attention for their high-quality novel view rendering, motivating research to address real-world challenges. A critical issue is…
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…
Improving Unsupervised Video Object Segmentation via Fake Flow Generation
Suhwan Cho, Minhyeok Lee, Jungho Lee +4
Unsupervised video object segmentation (VOS), also known as video salient object detection, aims to detect the most prominent object in a video at the pixel level. Recently, two-st…
Guided Slot Attention for Unsupervised Video Object Segmentation
Minhyeok Lee, Suhwan Cho, Dogyoon Lee +3
Unsupervised video object segmentation aims to segment the most prominent object in a video sequence. However, the existence of complex backgrounds and multiple foreground objects…