2 citations · 4 across the 14 of their papers we have counts for
14 papers
SceneFrom3D: Geometry-Conditioned Outdoor 3D Scene Generation via View Scheduling with Object-Level Control
Geonung Kim, Jeongeun Park, Nuri Ryu +2
Geometry-conditioned 3D scene generation enables the creation of 3D environments from user-provided geometry, offering direct control over scene structure and object layout. To gen…
HL-OutPaint: Coarse-to-Fine Video Outpainting for High-Resolution Long-Range Videos
Jeongeun Park, Janghyeok Han, Geonung Kim +4
Video outpainting generates plausible visual content beyond the original spatial extent of a video, playing a key role in adapting videos to diverse display formats. To support suc…
VideoFrom3D: 3D Scene Video Generation via Complementary Image and Video Diffusion Models
Geonung Kim, Janghyeok Han, Sunghyun Cho
In this paper, we propose VideoFrom3D, a novel framework for synthesizing high-quality 3D scene videos from coarse geometry, a camera trajectory, and a reference image. Our approac…
DC-VSR: Spatially and Temporally Consistent Video Super-Resolution with Video Diffusion Prior
Janghyeok Han, Gyujin Sim, Geonung Kim +4
Video super-resolution (VSR) aims to reconstruct a high-resolution (HR) video from a low-resolution (LR) counterpart. Achieving successful VSR requires producing realistic HR detai…
LayeringDiff: Layered Image Synthesis via Generation, then Disassembly with Generative Knowledge
Kyoungkook Kang, Gyujin Sim, Geonung Kim +3
Layers have become indispensable tools for professional artists, allowing them to build a hierarchical structure that enables independent control over individual visual elements. I…
RNA: Video Editing with ROI-based Neural Atlas
Jaekyeong Lee, Geonung Kim, Sunghyun Cho
With the recent growth of video-based Social Network Service (SNS) platforms, the demand for video editing among common users has increased. However, video editing can be challengi…
Diffusion Model Compression for Image-to-Image Translation
Geonung Kim, Beomsu Kim, Eunhyeok Park +1
As recent advances in large-scale Text-to-Image (T2I) diffusion models have yielded remarkable high-quality image generation, diverse downstream Image-to-Image (I2I) applications h…
ParamISP: Learned Forward and Inverse ISPs using Camera Parameters
Woohyeok Kim, Geonu Kim, Junyong Lee +3
RAW images are rarely shared mainly due to its excessive data size compared to their sRGB counterparts obtained by camera ISPs. Learning the forward and inverse processes of camera…
360 Reconstruction From a Single Image Using Space Carved Outpainting
Nuri Ryu, Minsu Gong, Geonung Kim +2
We introduce POP3D, a novel framework that creates a full -view 3D model from a single image. POP3D resolves two prominent issues that limit the single-view reconstructi…
Human Pose Estimation in Extremely Low-Light Conditions
Sohyun Lee, Jaesung Rim, Boseung Jeong +5
We study human pose estimation in extremely low-light images. This task is challenging due to the difficulty of collecting real low-light images with accurate labels, and severely…
Dr.3D: Adapting 3D GANs to Artistic Drawings
Wonjoon Jin, Nuri Ryu, Geonung Kim +2
While 3D GANs have recently demonstrated the high-quality synthesis of multi-view consistent images and 3D shapes, they are mainly restricted to photo-realistic human portraits. Th…
DynaGAN: Dynamic Few-shot Adaptation of GANs to Multiple Domains
Seongtae Kim, Kyoungkook Kang, Geonung Kim +2
Few-shot domain adaptation to multiple domains aims to learn a complex image distribution across multiple domains from a few training images. A naïve solution here is to train a se…
BigColor: Colorization using a Generative Color Prior for Natural Images
Geonung Kim, Kyoungkook Kang, Seongtae Kim +5
For realistic and vivid colorization, generative priors have recently been exploited. However, such generative priors often fail for in-the-wild complex images due to their limited…
Realistic Blur Synthesis for Learning Image Deblurring
Jaesung Rim, Geonung Kim, Jungeon Kim +3
Training learning-based deblurring methods demands a tremendous amount of blurred and sharp image pairs. Unfortunately, existing synthetic datasets are not realistic enough, and de…