6 citations · 8 across the 11 of their papers we have counts for
12 papers
Wispy to Voluminous: Prior-free Multi-view Capture of Strand-level Facial Hair
Jaeseong Lee, Giljoo Nam, Adrian Jarabo +1
Facial hair is a defining trait of personal identity, yet remains a critical bottleneck for digital avatars. Recent volumetric methods achieve photorealism but bake hair into the u…
The Fourth Challenge on Image Super-Resolution (4) at NTIRE 2026: Benchmark Results and Method Overview
Zheng Chen, Kai Liu, Jingkai Wang +150
This paper presents the NTIRE 2026 image super-resolution (4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026. The challenge aims to r…
TexAvatars : Hybrid Texel-3D Representations for Stable Rigging of Photorealistic Gaussian Head Avatars
Jaeseong Lee, Junyeong Ahn, Taewoong Kang +1
Constructing drivable and photorealistic 3D head avatars has become a central task in AR/XR, enabling immersive and expressive user experiences. With the emergence of high-fidelity…
Fair Generation without Unfair Distortions: Debiasing Text-to-Image Generation with Entanglement-Free Attention
Jeonghoon Park, Juyoung Lee, Chaeyeon Chung +3
Recent advancements in diffusion-based text-to-image (T2I) models have enabled the generation of high-quality and photorealistic images from text. However, they often exhibit socie…
SurFhead: Affine Rig Blending for Geometrically Accurate 2D Gaussian Surfel Head Avatars
Jaeseong Lee, Taewoong Kang, Marcel C. Bühler +5
Recent advancements in head avatar rendering using Gaussian primitives have achieved significantly high-fidelity results. Although precise head geometry is crucial for applications…
Effective Rank Analysis and Regularization for Enhanced 3D Gaussian Splatting
Junha Hyung, Susung Hong, Sungwon Hwang +3
3D reconstruction from multi-view images is one of the fundamental challenges in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a promising tec…
SelfSwapper: Self-Supervised Face Swapping via Shape Agnostic Masked AutoEncoder
Jaeseong Lee, Junha Hyung, Sohyun Jeong +1
Face swapping has gained significant attention for its varied applications. Most previous face swapping approaches have relied on the seesaw game training scheme, also known as the…
Expression Domain Translation Network for Cross-domain Head Reenactment
Taewoong Kang, Jeongsik Oh, Jaeseong Lee +2
Despite the remarkable advancements in head reenactment, the existing methods face challenges in cross-domain head reenactment, which aims to transfer human motions to domains outs…
PixelHuman: Animatable Neural Radiance Fields from Few Images
Gyumin Shim, Jaeseong Lee, Junha Hyung +1
In this paper, we propose PixelHuman, a novel human rendering model that generates animatable human scenes from a few images of a person with unseen identity, views, and poses. Pre…
RobustSwap: A Simple yet Robust Face Swapping Model against Attribute Leakage
Jaeseong Lee, Taewoo Kim, Sunghyun Park +2
Face swapping aims at injecting a source image's identity (i.e., facial features) into a target image, while strictly preserving the target's attributes, which are irrelevant to id…
AnimeCeleb: Large-Scale Animation CelebHeads Dataset for Head Reenactment
Kangyeol Kim, Sunghyun Park, Jaeseong Lee +3
We present a novel Animation CelebHeads dataset (AnimeCeleb) to address an animation head reenactment. Different from previous animation head datasets, we utilize 3D animation mode…
Adversarial Video Compression Guided by Soft Edge Detection
Sungsoo Kim, Jin Soo Park, Christos G. Bampis +4
We propose a video compression framework using conditional Generative Adversarial Networks (GANs). We rely on two encoders: one that deploys a standard video codec and another whic…