1 citations · 2 across the 4 of their papers we have counts for
5 papers
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…
T2LM: Long-Term 3D Human Motion Generation from Multiple Sentences
Taeryung Lee, Fabien Baradel, Thomas Lucas +2
In this paper, we address the challenging problem of long-term 3D human motion generation. Specifically, we aim to generate a long sequence of smoothly connected actions from a str…
Human Part-wise 3D Motion Context Learning for Sign Language Recognition
Taeryung Lee, Yeonguk Oh, Kyoung Mu Lee
In this paper, we propose P3D, the human part-wise motion context learning framework for sign language recognition. Our main contributions lie in two dimensions: learning the part-…
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,…
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…