40 citations · 75 across the 18 of their papers we have counts for
18 papers · 1 filter
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…
DiTTo: Scalable Order-aware All-in-One Image Restoration Agent
Seungho Choi, Jihyong Oh
Real-world images rarely suffer from a single degradation, and the order in which degradations are removed substantially affects the final restoration quality, motivating agent-bas…
MotionGrounder: Grounded Multi-Object Motion Transfer via Diffusion Transformer
Samuel Teodoro, Yun Chen, Agus Gunawan +3
Motion transfer enables controllable video generation by transferring temporal dynamics from a reference video to synthesize a new video conditioned on a target caption. However, e…
EcoSplat: Efficiency-controllable Feed-forward 3D Gaussian Splatting from Multi-view Images
Jongmin Park, Minh-Quan Viet Bui, Juan Luis Gonzalez Bello +3
Feed-forward 3D Gaussian Splatting (3DGS) enables efficient one-pass scene reconstruction, providing 3D representations for novel view synthesis without per-scene optimization. How…
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…
I-INR: Iterative Implicit Neural Representations
Ali Haider, Muhammad Salman Ali, Maryam Qamar +5
Implicit Neural Representations (INRs) have revolutionized signal processing and computer vision by modeling signals as continuous, differentiable functions parameterized by neural…
MoBGS: Motion Deblurring Dynamic 3D Gaussian Splatting for Blurry Monocular Video
Minh-Quan Viet Bui, Jongmin Park, Juan Luis Gonzalez Bello +3
We present MoBGS, a novel motion deblurring 3D Gaussian Splatting (3DGS) framework capable of reconstructing sharp and high-quality novel spatio-temporal views from blurry monocula…
MoDec-GS: Global-to-Local Motion Decomposition and Temporal Interval Adjustment for Compact Dynamic 3D Gaussian Splatting
Sangwoon Kwak, Joonsoo Kim, Jun Young Jeong +3
3D Gaussian Splatting (3DGS) has made significant strides in scene representation and neural rendering, with intense efforts focused on adapting it for dynamic scenes. Despite deli…
SplineGS: Robust Motion-Adaptive Spline for Real-Time Dynamic 3D Gaussians from Monocular Video
Jongmin Park, Minh-Quan Viet Bui, Juan Luis Gonzalez Bello +3
Synthesizing novel views from in-the-wild monocular videos is challenging due to scene dynamics and the lack of multi-view cues. To address this, we propose SplineGS, a COLMAP-free…
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…
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…
DeMFI: Deep Joint Deblurring and Multi-Frame Interpolation with Flow-Guided Attentive Correlation and Recursive Boosting
Jihyong Oh, Munchurl Kim
In this paper, we propose a novel joint deblurring and multi-frame interpolation (DeMFI) framework, called DeMFI-Net, which accurately converts blurry videos of lower-frame-rate to…
PeaceGAN: A GAN-based Multi-Task Learning Method for SAR Target Image Generation with a Pose Estimator and an Auxiliary Classifier
Jihyong Oh, Munchurl Kim
Although Generative Adversarial Networks (GANs) are successfully applied to diverse fields, training GANs on synthetic aperture radar (SAR) data is a challenging task mostly due to…
XVFI: eXtreme Video Frame Interpolation
Hyeonjun Sim, Jihyong Oh, Munchurl Kim
In this paper, we firstly present a dataset (X4K1000FPS) of 4K videos of 1000 fps with the extreme motion to the research community for video frame interpolation (VFI), and propose…
FISR: Deep Joint Frame Interpolation and Super-Resolution with a Multi-scale Temporal Loss
Soo Ye Kim, Jihyong Oh, Munchurl Kim
Super-resolution (SR) has been widely used to convert low-resolution legacy videos to high-resolution (HR) ones, to suit the increasing resolution of displays (e.g. UHD TVs). Howev…