36 citations · 103 across the 27 of their papers we have counts for
30 papers
Zero-Shot Reconstruction of Animatable 3D Avatars with Cloth Dynamics from a Single Image
Joohyun Kwon, Geonhee Sim, Gyeongsik Moon
Existing single-image 3D human avatar methods primarily rely on rigid joint transformations, limiting their ability to model realistic cloth dynamics. We present DynaAvatar, a zero…
Enhancing Hands in 3D Whole-Body Pose Estimation with Conditional Hands Modulator
Gyeongsik Moon
Accurately recovering hand poses within the body context remains a major challenge in 3D whole-body pose estimation. This difficulty arises from a fundamental supervision gap: whol…
PARTE: Part-Guided Texturing for 3D Human Reconstruction from a Single Image
Hyeongjin Nam, Donghwan Kim, Gyeongsik Moon +1
The misaligned human texture across different human parts is one of the main limitations of existing 3D human reconstruction methods. Each human part, such as a jacket or pants, sh…
SIGNER: Temporally Grounded Sign Language Generation via Time-Resolved Conditioning
Taeryung Lee, Hyeongjin Nam, Gyeongsik Moon +1
Sign language generation (SLG), also known as text-to-sign generation, aims to bridge the communication gap between signers and non-signers. Unlike many other generative tasks, SLG…
Joint Reconstruction of 3D Human and Object via Contact-Based Refinement Transformer
Hyeongjin Nam, Daniel Sungho Jung, Gyeongsik Moon +1
Human-object contact serves as a strong cue to understand how humans physically interact with objects. Nevertheless, it is not widely explored to utilize human-object contact infor…
Extract-and-Adaptation Network for 3D Interacting Hand Mesh Recovery
JoonKyu Park, Daniel Sungho Jung, Gyeongsik Moon +1
Understanding how two hands interact with each other is a key component of accurate 3D interacting hand mesh recovery. However, recent Transformer-based methods struggle to learn t…
Three Recipes for Better 3D Pseudo-GTs of 3D Human Mesh Estimation in the Wild
Gyeongsik Moon, Hongsuk Choi, Sanghyuk Chun +2
Recovering 3D human mesh in the wild is greatly challenging as in-the-wild (ITW) datasets provide only 2D pose ground truths (GTs). Recently, 3D pseudo-GTs have been widely used to…
Recovering 3D Hand Mesh Sequence from a Single Blurry Image: A New Dataset and Temporal Unfolding
Yeonguk Oh, JoonKyu Park, Jaeha Kim +2
Hands, one of the most dynamic parts of our body, suffer from blur due to their active movements. However, previous 3D hand mesh recovery methods have mainly focused on sharp hand…
Rethinking Self-Supervised Visual Representation Learning in Pre-training for 3D Human Pose and Shape Estimation
Hongsuk Choi, Hyeongjin Nam, Taeryung Lee +2
Recently, a few self-supervised representation learning (SSL) methods have outperformed the ImageNet classification pre-training for vision tasks such as object detection. However,…
Bringing Inputs to Shared Domains for 3D Interacting Hands Recovery in the Wild
Gyeongsik Moon
Despite recent achievements, existing 3D interacting hands recovery methods have shown results mainly on motion capture (MoCap) environments, not on in-the-wild (ITW) ones. This is…
MultiAct: Long-Term 3D Human Motion Generation from Multiple Action Labels
Taeryung Lee, Gyeongsik Moon, Kyoung Mu Lee
We tackle the problem of generating long-term 3D human motion from multiple action labels. Two main previous approaches, such as action- and motion-conditioned methods, have limita…
MonoNHR: Monocular Neural Human Renderer
Hongsuk Choi, Gyeongsik Moon, Matthieu Armando +3
Existing neural human rendering methods struggle with a single image input due to the lack of information in invisible areas and the depth ambiguity of pixels in visible areas. In…
3D Clothed Human Reconstruction in the Wild
Gyeongsik Moon, Hyeongjin Nam, Takaaki Shiratori +1
Although much progress has been made in 3D clothed human reconstruction, most of the existing methods fail to produce robust results from in-the-wild images, which contain diverse…
HandOccNet: Occlusion-Robust 3D Hand Mesh Estimation Network
JoonKyu Park, Yeonguk Oh, Gyeongsik Moon +2
Hands are often severely occluded by objects, which makes 3D hand mesh estimation challenging. Previous works often have disregarded information at occluded regions. However, we ar…
Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes
Hongsuk Choi, Gyeongsik Moon, JoonKyu Park +1
We consider the problem of recovering a single person's 3D human mesh from in-the-wild crowded scenes. While much progress has been in 3D human mesh estimation, existing methods st…
Accurate 3D Hand Pose Estimation for Whole-Body 3D Human Mesh Estimation
Gyeongsik Moon, Hongsuk Choi, Kyoung Mu Lee
Whole-body 3D human mesh estimation aims to reconstruct the 3D human body, hands, and face simultaneously. Although several methods have been proposed, accurate prediction of 3D ha…
NeuralAnnot: Neural Annotator for 3D Human Mesh Training Sets
Gyeongsik Moon, Hongsuk Choi, Kyoung Mu Lee
Most 3D human mesh regressors are fully supervised with 3D pseudo-GT human model parameters and weakly supervised with GT 2D/3D joint coordinates as the 3D pseudo-GTs bring great p…
Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video
Hongsuk Choi, Gyeongsik Moon, Ju Yong Chang +1
Despite the recent success of single image-based 3D human pose and shape estimation methods, recovering temporally consistent and smooth 3D human motion from a video is still chall…
InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Image
Gyeongsik Moon, Shoou-i Yu, He Wen +2
Analysis of hand-hand interactions is a crucial step towards better understanding human behavior. However, most researches in 3D hand pose estimation have focused on the isolated s…
DeepHandMesh: A Weakly-supervised Deep Encoder-Decoder Framework for High-fidelity Hand Mesh Modeling
Gyeongsik Moon, Takaaki Shiratori, Kyoung Mu Lee
Human hands play a central role in interacting with other people and objects. For realistic replication of such hand motions, high-fidelity hand meshes have to be reconstructed. In…
A Spectrometric Approach to Measuring the Rayleigh Scattering Length for Liquid Scintillator Detectors
S. S. Gokhale, R. Rosero, R. Diaz Perez +3
Good optical transparency is a fundamental requirement of liquid scintillator (LS) detectors. Characterizing the transparency of a liquid scintillator to its own emitted light is a…
I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB Image
Gyeongsik Moon, Kyoung Mu Lee
Most of the previous image-based 3D human pose and mesh estimation methods estimate parameters of the human mesh model from an input image. However, directly regressing the paramet…
IntegralAction: Pose-driven Feature Integration for Robust Human Action Recognition in Videos
Gyeongsik Moon, Heeseung Kwon, Kyoung Mu Lee +1
Most current action recognition methods heavily rely on appearance information by taking an RGB sequence of entire image regions as input. While being effective in exploiting conte…
PoseLifter: Absolute 3D human pose lifting network from a single noisy 2D human pose
Ju Yong Chang, Gyeongsik Moon, Kyoung Mu Lee
This study presents a new network (i.e., PoseLifter) that can lift a 2D human pose to an absolute 3D pose in a camera coordinate system. The proposed network estimates the absolute…