Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Pinyoanuntapong, Ekkasit"'
Autor:
Pinyoanuntapong, Ekkasit, Saleem, Muhammad Usama, Karunratanakul, Korrawe, Wang, Pu, Xue, Hongfei, Chen, Chen, Guo, Chuan, Cao, Junli, Ren, Jian, Tulyakov, Sergey
Recent advances in motion diffusion models have enabled spatially controllable text-to-motion generation. However, despite achieving acceptable control precision, these models suffer from generation speed and fidelity limitations. To address these ch
Externí odkaz:
http://arxiv.org/abs/2410.10780
Autor:
Pinyoanuntapong, Ekkasit, Saleem, Muhammad Usama, Wang, Pu, Lee, Minwoo, Das, Srijan, Chen, Chen
Generating human motion from text has been dominated by denoising motion models either through diffusion or generative masking process. However, these models face great limitations in usability by requiring prior knowledge of the motion length. Conve
Externí odkaz:
http://arxiv.org/abs/2403.19435
Recent advances in text-to-motion generation using diffusion and autoregressive models have shown promising results. However, these models often suffer from a trade-off between real-time performance, high fidelity, and motion editability. To address
Externí odkaz:
http://arxiv.org/abs/2312.03596
In this research, we address the challenge faced by existing deep learning-based human mesh reconstruction methods in balancing accuracy and computational efficiency. These methods typically prioritize accuracy, resulting in large network sizes and e
Externí odkaz:
http://arxiv.org/abs/2301.13403
Autor:
Pinyoanuntapong, Ekkasit, Ali, Ayman, Jakkala, Kalvik, Wang, Pu, Lee, Minwoo, Peng, Qucheng, Chen, Chen, Sun, Zhi
mmWave radar-based gait recognition is a novel user identification method that captures human gait biometrics from mmWave radar return signals. This technology offers privacy protection and is resilient to weather and lighting conditions. However, it
Externí odkaz:
http://arxiv.org/abs/2301.13384
Recently, there has been a remarkable increase in the interest towards skeleton-based action recognition within the research community, owing to its various advantageous features, including computational efficiency, representative features, and illum
Externí odkaz:
http://arxiv.org/abs/2301.13360
Most existing gait recognition methods are appearance-based, which rely on the silhouettes extracted from the video data of human walking activities. The less-investigated skeleton-based gait recognition methods directly learn the gait dynamics from
Externí odkaz:
http://arxiv.org/abs/2210.15491
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Most existing gait recognition methods are appearance-based, which rely on the silhouettes extracted from the video data of human walking activities. The less-investigated skeleton-based gait recognition methods directly learn the gait dynamics from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::505a5a47a3548fa7f2d1929ae2193c54
https://doi.org/10.1109/icassp49357.2023.10096917
https://doi.org/10.1109/icassp49357.2023.10096917
