3 citations · 4 across the 8 of their papers we have counts for
9 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…
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…
PRIMEdit: Probability Redistribution for Instance-Aware Multi-Object Video Editing With a New Benchmark Dataset
Samuel Teodoro, Agus Gunawan, Soo Ye Kim +2
Recent Artificial Intelligence (AI)-based video editing has enabled users to edit videos through simple text prompts, significantly simplifying the editing process. However, recent…
BiM-VFI: Bidirectional Motion Field-Guided Frame Interpolation for Video with Non-uniform Motions
Wonyong Seo, Jihyong Oh, Munchurl Kim
Existing Video Frame interpolation (VFI) models tend to suffer from time-to-location ambiguity when trained with video of non-uniform motions, such as accelerating, decelerating, a…
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…
FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurring
Geunhyuk Youk, Jihyong Oh, Munchurl Kim
We present a joint learning scheme of video super-resolution and deblurring, called VSRDB, to restore clean high-resolution (HR) videos from blurry low-resolution (LR) ones. This j…
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…
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…