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pro vyhledávání: '"YU Hui"'
Despite recent advances in stereo matching, the extension to intricate underwater settings remains unexplored, primarily owing to: 1) the reduced visibility, low contrast, and other adverse effects of underwater images; 2) the difficulty in obtaining
Externí odkaz:
http://arxiv.org/abs/2409.01782
3D Gaussian Splatting has recently emerged as a powerful representation that can synthesize remarkable novel views using consistent multi-view images as input. However, we notice that images captured in dark environments where the scenes are not full
Externí odkaz:
http://arxiv.org/abs/2408.09130
Providing timely support and intervention is crucial in mental health settings. As the need to engage youth comfortable with texting increases, mental health providers are exploring and adopting text-based media such as chatbots, community-based foru
Externí odkaz:
http://arxiv.org/abs/2406.11135
Although recent masked image modeling (MIM)-based HSI-LiDAR/SAR classification methods have gradually recognized the importance of the spectral information, they have not adequately addressed the redundancy among different spectra, resulting in infor
Externí odkaz:
http://arxiv.org/abs/2406.01235
Source-free Unsupervised Domain Adaptation (SFDA) aims to classify target samples by only accessing a pre-trained source model and unlabelled target samples. Since no source data is available, transferring the knowledge from the source domain to the
Externí odkaz:
http://arxiv.org/abs/2405.06916
Publikováno v:
New J. Phys. 26, 073037 (2024)
Coherence is intrinsically related to projective measurement. When the fixed projective measurement involves higher-rank projectors, the coherence resource is referred to as block coherence, which comes from the superposition of orthogonal subspaces.
Externí odkaz:
http://arxiv.org/abs/2404.13526
Autor:
Sheng, Jenny, Lin, Matthieu, Zhao, Andrew, Pruvost, Kevin, Wen, Yu-Hui, Li, Yangguang, Huang, Gao, Liu, Yong-Jin
This paper presents an exploration of preference learning in text-to-motion generation. We find that current improvements in text-to-motion generation still rely on datasets requiring expert labelers with motion capture systems. Instead, learning fro
Externí odkaz:
http://arxiv.org/abs/2404.09445
Akademický článek
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In the fast-evolving field of medical image analysis, Deep Learning (DL)-based methods have achieved tremendous success. However, these methods require plaintext data for training and inference stages, raising privacy concerns, especially in the sens
Externí odkaz:
http://arxiv.org/abs/2403.16473
Multi-view action clustering leverages the complementary information from different camera views to enhance the clustering performance. Although existing approaches have achieved significant progress, they assume all camera views are available in adv
Externí odkaz:
http://arxiv.org/abs/2404.07962