Zobrazeno 1 - 10
of 22 448
pro vyhledávání: '"Yu, Tao"'
Light field microscopy (LFM) has been widely utilized in various fields for its capability to efficiently capture high-resolution 3D scenes. Despite the rapid advancements in neural representations, there are few methods specifically tailored for mic
Externí odkaz:
http://arxiv.org/abs/2409.18223
Autor:
Li, Peng, Zheng, Wangguandong, Liu, Yuan, Yu, Tao, Li, Yangguang, Qi, Xingqun, Li, Mengfei, Chi, Xiaowei, Xia, Siyu, Xue, Wei, Luo, Wenhan, Liu, Qifeng, Guo, Yike
Detailed and photorealistic 3D human modeling is essential for various applications and has seen tremendous progress. However, full-body reconstruction from a monocular RGB image remains challenging due to the ill-posed nature of the problem and soph
Externí odkaz:
http://arxiv.org/abs/2409.10141
Digital twin (DT) technology can replicate physical entities in cyberspace. A mobility DT digitalizes connected and autonomous vehicles (CAVs) and their surrounding traffic environment, allowing to monitor the maneuvering and distribution of CAVs in
Externí odkaz:
http://arxiv.org/abs/2409.00040
Autor:
Zheng, Ruichen, Yu, Tao
Neural implicit representation, the parameterization of distance function as a coordinate neural field, has emerged as a promising lead in tackling surface reconstruction from unoriented point clouds. To enforce consistent orientation, existing metho
Externí odkaz:
http://arxiv.org/abs/2408.00303
Transfer learning has emerged as a highly sought-after and actively pursued research area within the statistical community. The core concept of transfer learning involves leveraging insights and information from auxiliary datasets to enhance the anal
Externí odkaz:
http://arxiv.org/abs/2407.21682
Exceptional points with coalescence of eigenvalues and eigenvectors are spectral singularities in the parameter space, achieving which often needs fine-tuning of parameters in quantum systems. We predict a persistent realization of nodal magnon-photo
Externí odkaz:
http://arxiv.org/abs/2407.21597
Due to the increasing complexity of chip design, existing placement methods still have many shortcomings in dealing with macro cells coverage and optimization efficiency. Aiming at the problems of layout overlap, inferior performance, and low optimiz
Externí odkaz:
http://arxiv.org/abs/2407.18499
Deep learning, especially convolutional neural networks (CNNs) and Transformer architectures, have become the focus of extensive research in medical image segmentation, achieving impressive results. However, CNNs come with inductive biases that limit
Externí odkaz:
http://arxiv.org/abs/2407.18070
In recent studies on domain adaptation, significant emphasis has been placed on the advancement of learning shared knowledge from a source domain to a target domain. Recently, the large vision-language pre-trained model, i.e., CLIP has shown strong a
Externí odkaz:
http://arxiv.org/abs/2407.15173
Autor:
Su, Hongjin, Yen, Howard, Xia, Mengzhou, Shi, Weijia, Muennighoff, Niklas, Wang, Han-yu, Liu, Haisu, Shi, Quan, Siegel, Zachary S., Tang, Michael, Sun, Ruoxi, Yoon, Jinsung, Arik, Sercan O., Chen, Danqi, Yu, Tao
Existing retrieval benchmarks primarily consist of information-seeking queries (e.g., aggregated questions from search engines) where keyword or semantic-based retrieval is usually sufficient. However, many complex real-world queries require in-depth
Externí odkaz:
http://arxiv.org/abs/2407.12883