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pro vyhledávání: '"Chi, Seunggeun"'
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 hea
Externí odkaz:
http://arxiv.org/abs/2411.03561
Autor:
Chi, Seunggeun, Chi, Hyung-gun, Ma, Hengbo, Agarwal, Nakul, Siddiqui, Faizan, Ramani, Karthik, Lee, Kwonjoon
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 cha
Externí odkaz:
http://arxiv.org/abs/2407.14502
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 classificatio
Externí odkaz:
http://arxiv.org/abs/2310.10547
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence [IEEE Trans Pattern Anal Mach Intell] 2024 Sep 26; Vol. PP. Date of Electronic Publication: 2024 Sep 26.
