78 citations · 109 across the 5 of their papers we have counts for
5 papers
ELMO: Enhanced Real-time LiDAR Motion Capture through Upsampling
Deok-Kyeong Jang, Dongseok Yang, Deok-Yun Jang +3
This paper introduces ELMO, a real-time upsampling motion capture framework designed for a single LiDAR sensor. Modeled as a conditional autoregressive transformer-based upsampling…
MOCHA: Real-Time Motion Characterization via Context Matching
Deok-Kyeong Jang, Yuting Ye, Jungdam Won +1
Transforming neutral, characterless input motions to embody the distinct style of a notable character in real time is highly compelling for character animation. This paper introduc…
MOVIN: Real-time Motion Capture using a Single LiDAR
Deok-Kyeong Jang, Dongseok Yang, Deok-Yun Jang +3
Recent advancements in technology have brought forth new forms of interactive applications, such as the social metaverse, where end users interact with each other through their vir…
Motion Puzzle: Arbitrary Motion Style Transfer by Body Part
Deok-Kyeong Jang, Soomin Park, Sung-Hee Lee
This paper presents Motion Puzzle, a novel motion style transfer network that advances the state-of-the-art in several important respects. The Motion Puzzle is the first that can c…
Constructing Human Motion Manifold with Sequential Networks
Deok-Kyeong Jang, Sung-Hee Lee
This paper presents a novel recurrent neural network-based method to construct a latent motion manifold that can represent a wide range of human motions in a long sequence. We intr…