8 papers
AVSR-Diff: Scale-Agnostic Diffusion Priors for Temporally Consistent Arbitrary-Scale Video Super-Resolution
Geunhyuk Youk, Jeonghyeok Do, Dayeon Kim +2
Diffusion models have significantly advanced video super-resolution (VSR) but remain largely constrained to fixed upsampling scales. Conversely, while coordinate-based arbitrary-sc…
FMA-Net++: Motion- and Exposure-Aware Joint Video Super-Resolution and Deblurring
Geunhyuk Youk, Jihyong Oh, Munchurl Kim
Joint video super-resolution and deblurring (VSRDB) requires both efficient long-range temporal modeling and robustness to frame-wise exposure-duration variation, which changes the…
COMPASS: High-Efficiency Deep Image Compression with Arbitrary-scale Spatial Scalability
Jongmin Park, Jooyoung Lee, Munchurl Kim
Recently, neural network (NN)-based image compression studies have actively been made and has shown impressive performance in comparison to traditional methods. However, most of th…
DeepHQ: Learned Hierarchical Quantizer for Progressive Deep Image Coding
Jooyoung Lee, Se Yoon Jeong, Munchurl Kim
Unlike fixed- or variable-rate image coding, progressive image coding (PIC) aims to compress various qualities of images into a single bitstream, increasing the versatility of bits…
OmniText: A Training-Free Generalist for Controllable Text-Image Manipulation
Agus Gunawan, Samuel Teodoro, Yun Chen +3
Recent advancements in diffusion-based text synthesis have demonstrated significant performance in inserting and editing text within images via inpainting. However, despite the pot…
MoBluRF: Motion Deblurring Neural Radiance Fields for Blurry Monocular Video
Minh-Quan Viet Bui, Jongmin Park, Jihyong Oh +1
Neural Radiance Fields (NeRF), initially developed for static scenes, have inspired many video novel view synthesis techniques. However, the challenge for video view synthesis aris…