4 papers
Language-Assisted Super-Resolution from Real-World Low-Resolution Patches
Joonkyu Park, Kyoung Mu Lee
Single image super-resolution aims to reconstruct high-resolution (HR) images from low-resolution (LR) inputs. Training SR models typically requires paired HR-LR data, which is dif…
GS-Blur: A 3D Scene-Based Dataset for Realistic Image Deblurring
Dongwoo Lee, Joonkyu Park, Kyoung Mu Lee
To train a deblurring network, an appropriate dataset with paired blurry and sharp images is essential. Existing datasets collect blurry images either synthetically by aggregating…
Rethinking RGB Color Representation for Image Restoration Models
Jaerin Lee, JoonKyu Park, Sungyong Baik +1
Image restoration models are typically trained with a pixel-wise distance loss defined over the RGB color representation space, which is well known to be a source of blurry and unr…
3DHR-Co: A Collaborative Test-time Refinement Framework for In-the-Wild 3D Human-Body Reconstruction Task
Jonathan Samuel Lumentut, Kyoung Mu Lee
The field of 3D human-body reconstruction (abbreviated as 3DHR) that utilizes parametric pose and shape representations has witnessed significant advancements in recent years. Howe…