by Seunggeun Chi | Sep 27, 2024 | 2024, Karthik Ramani, Recent Publications, Seunggeun Chi
We study the problem of estimating the body movements of a camera wearer from egocentric videos. Current methods for ego-body pose estimation rely on temporally dense sensor data, such as IMU measurements from spatially sparse body parts like the head and hands....
by Seunggeun Chi | Sep 26, 2024 | 2024, Featured Publications, Hyunggun Chi, Karthik Ramani, Karthik Ramani, Publications, Recent Publications, Seunggeun Chi
We introduce the Multi-Motion Discrete Diffusion Models (M2D2M), a novel approach for human motion generation from textual descriptions of multiple actions, utilizing the strengths of discrete diffusion models. This approach adeptly addresses the challenge of...
by Seunggeun Chi | Sep 18, 2024 | 2024, Hyunggun Chi, Karthik Ramani, Publications, Recent Publications, Seunggeun Chi
Skeleton-based action recognition has made significant advancements recently, with models like InfoGCN showcasing remarkable accuracy. However, these models exhibit a key limitation: they necessitate complete action observation prior to classification, which...
by Hyung-gun Chi | Feb 24, 2023 | 2023, Hyunggun Chi, Karthik Ramani, Publications, Seunggeun Chi
Accurately estimating the human pose is an essential task for many applications in robotics. However, existing pose estimation methods suffer from poor performance when occlusion occurs. Recent advances in NLP have been very successful in predicting the missing words...
by Hyung-gun Chi | Apr 19, 2022 | 2022, Hyunggun Chi, Karthik Ramani, Publications, Recent Publications, Seunggeun Chi
Human skeleton-based action recognition offers a valuable means to understand the intricacies of human behavior because it can handle the complex relationships between physical constraints and intention. Although several studies have focused on encoding a skeleton,...
