Zobrazeno 1 - 10
of 225
pro vyhledávání: '"Shao, Jiawei"'
The feed-forward based 3D Gaussian Splatting method has demonstrated exceptional capability in real-time human novel view synthesis. However, existing approaches are restricted to dense viewpoint settings, which limits their flexibility in free-viewp
Externí odkaz:
http://arxiv.org/abs/2410.01425
Wireless networks are increasingly facing challenges due to their expanding scale and complexity. These challenges underscore the need for advanced AI-driven strategies, particularly in the upcoming 6G networks. In this article, we introduce Wireless
Externí odkaz:
http://arxiv.org/abs/2409.07964
Autor:
Xu, Xin, Shao, Jiawei
Planar Tur\'an number $ex_{\mathcal{P}}(n,H)$ of $H$ is the maximum number of edges in an $n$-vertex planar graph which does not contain $H$ as a subgraph. Ghosh, Gy\H{o}ri, Paulos and Xiao initiated the topic of the planar Tur\'an number for double
Externí odkaz:
http://arxiv.org/abs/2409.01016
Vehicle-to-infrastructure (V2I) cooperative perception plays a crucial role in autonomous driving scenarios. Despite its potential to improve perception accuracy and robustness, the large amount of raw sensor data inevitably results in high communica
Externí odkaz:
http://arxiv.org/abs/2407.20748
With the rapid advancement of stereo vision technologies, stereo image compression has emerged as a crucial field that continues to draw significant attention. Previous approaches have primarily employed a unidirectional paradigm, where the compressi
Externí odkaz:
http://arxiv.org/abs/2407.10632
Retrieval augmented generation has revolutionized large language model (LLM) outputs by providing factual supports. Nevertheless, it struggles to capture all the necessary knowledge for complex reasoning questions. Existing retrieval methods typicall
Externí odkaz:
http://arxiv.org/abs/2406.06572
The rapid evolution of wireless technologies and the growing complexity of network infrastructures necessitate a paradigm shift in how communication networks are designed, configured, and managed. Recent advancements in Large Language Models (LLMs) h
Externí odkaz:
http://arxiv.org/abs/2405.17053
Task-oriented communication aims to extract and transmit task-relevant information to significantly reduce the communication overhead and transmission latency. However, the unpredictable distribution shifts between training and test data, including d
Externí odkaz:
http://arxiv.org/abs/2405.09514
Autor:
Zhang, Xinjie, Gao, Shenyuan, Liu, Zhening, Shao, Jiawei, Ge, Xingtong, He, Dailan, Xu, Tongda, Wang, Yan, Zhang, Jun
Existing learning-based stereo image codec adopt sophisticated transformation with simple entropy models derived from single image codecs to encode latent representations. However, those entropy models struggle to effectively capture the spatial-disp
Externí odkaz:
http://arxiv.org/abs/2403.08505
Federated learning (FL) is a distributed learning paradigm that maximizes the potential of data-driven models for edge devices without sharing their raw data. However, devices often have non-independent and identically distributed (non-IID) data, mea
Externí odkaz:
http://arxiv.org/abs/2308.15786