Human Part-wise 3D Motion Context Learning for Sign Language Recognition

no code implementations • ICCV 2023 • Taeryung Lee, Yeonguk Oh, Kyoung Mu Lee

In order to utilize part-wise motion context, we propose the alternating combination of a part-wise encoding Transformer (PET) and a whole-body encoding Transformer (WET).

Sign Language Recognition

Cyclic Test-Time Adaptation on Monocular Video for 3D Human Mesh Reconstruction

1 code implementation • ICCV 2023 • Hyeongjin Nam, Daniel Sungho Jung, Yeonguk Oh, Kyoung Mu Lee

To overcome the above issues, we introduce CycleAdapt, which cyclically adapts two networks: a human mesh reconstruction network (HMRNet) and a human motion denoising network (MDNet), given a test video.

3D Human Pose Estimation Denoising +1

Recovering 3D Hand Mesh Sequence from a Single Blurry Image: A New Dataset and Temporal Unfolding

1 code implementation • CVPR 2023 • Yeonguk Oh, JoonKyu Park, Jaeha Kim, Gyeongsik Moon, Kyoung Mu Lee

In addition to the new dataset, we propose BlurHandNet, a baseline network for accurate 3D hand mesh recovery from a blurry hand image.

HandOccNet: Occlusion-Robust 3D Hand Mesh Estimation Network

no code implementations • CVPR 2022 • JoonKyu Park, Yeonguk Oh, Gyeongsik Moon, Hongsuk Choi, Kyoung Mu Lee

However, we argue that occluded regions have strong correlations with hands so that they can provide highly beneficial information for complete 3D hand mesh estimation.

hand-object pose