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pro vyhledávání: '"Chen Wei-Ting"'
Segment Anything Model (SAM) has emerged as a transformative approach in image segmentation, acclaimed for its robust zero-shot segmentation capabilities and flexible prompting system. Nonetheless, its performance is challenged by images with degrade
Externí odkaz:
http://arxiv.org/abs/2406.09627
Generic Face Image Quality Assessment (GFIQA) evaluates the perceptual quality of facial images, which is crucial in improving image restoration algorithms and selecting high-quality face images for downstream tasks. We present a novel transformer-ba
Externí odkaz:
http://arxiv.org/abs/2406.09622
Crowd counting and localization have become increasingly important in computer vision due to their wide-ranging applications. While point-based strategies have been widely used in crowd counting methods, they face a significant challenge, i.e., the l
Externí odkaz:
http://arxiv.org/abs/2405.10589
Crowd counting has recently attracted significant attention in the field of computer vision due to its wide applications to image understanding. Numerous methods have been proposed and achieved state-of-the-art performance for real-world tasks. Howev
Externí odkaz:
http://arxiv.org/abs/2306.01209
Neural radiance fields (NeRFs) have demonstrated state-of-the-art performance for 3D computer vision tasks, including novel view synthesis and 3D shape reconstruction. However, these methods fail in adverse weather conditions. To address this challen
Externí odkaz:
http://arxiv.org/abs/2303.11364
Autor:
Chen, Wei-Ting, Chen, I-Hsiang, Yeh, Chih-Yuan, Yang, Hao-Hsiang, Chang, Hua-En, Ding, Jian-Jiun, Kuo, Sy-Yen
Recently, vehicle similarity learning, also called re-identification (ReID), has attracted significant attention in computer vision. Several algorithms have been developed and obtained considerable success. However, most existing methods have unpleas
Externí odkaz:
http://arxiv.org/abs/2209.08630
Autor:
Radtke, Marcela D., Chen, Wei-Ting, Xiao, Lan, Rodriguez Espinosa, Patricia, Orizaga, Marcela, Thomas, Tainayah, Venditti, Elizabeth, Yaroch, Amy L., Zepada, Kenia, Rosas, Lisa G., Tester, June
Publikováno v:
In Contemporary Clinical Trials November 2024 146
Autor:
Lin, Jr-Jiun1 (AUTHOR), Chen, Wei-Ting1 (AUTHOR), Ong, Hooi-Nee1 (AUTHOR), Hung, Chi-Sheng2 (AUTHOR), Chang, Wei-Tien1 (AUTHOR), Huang, Chien-Hua1 (AUTHOR), Tsai, Min-Shan1 (AUTHOR) mshanmshan@gmail.com
Publikováno v:
Journal of Clinical Medicine. Sep2024, Vol. 13 Issue 17, p5293. 11p.
Images acquired from rainy scenes usually suffer from bad visibility which may damage the performance of computer vision applications. The rainy scenarios can be categorized into two classes: moderate rain and heavy rain scenes. Moderate rain scene m
Externí odkaz:
http://arxiv.org/abs/2111.12925
Autor:
Jung, Chau-Ren, Chen, Wei, Chen, Wei-Ting, Su, Shih-Hao, Chen, Bo-Ting, Chang, Ling, Hwang, Bing-Fang
Publikováno v:
In Atmospheric Environment 15 August 2024 331