Zobrazeno 1 - 10
of 23 323
pro vyhledávání: '"Feng, Wei"'
Traditional point cloud registration (PCR) methods for feature matching often employ the nearest neighbor policy. This leads to many-to-one matches and numerous potential inliers without any corresponding point. Recently, some approaches have framed
Externí odkaz:
http://arxiv.org/abs/2412.04855
Confidential Computing has emerged to address data security challenges in cloud-centric deployments by protecting data in use through hardware-level isolation. However, reliance on a single hardware root of trust (RoT) limits user confidence in cloud
Externí odkaz:
http://arxiv.org/abs/2412.03842
The origin of the binary black hole mergers observed by LIGO-Virgo-KAGRA (LVK) remains an open question. We calculate the merger rate from primordial black holes (PBHs) within the density spike around supermassive black holes (SMBHs) at the center of
Externí odkaz:
http://arxiv.org/abs/2411.05065
The achievement of spectral super-resolution sensing is critically important for a variety of applications, such as radar, remote sensing, and wireless communication. However, in compressed spectrum sensing, challenges such as spectrum leakage and th
Externí odkaz:
http://arxiv.org/abs/2411.02700
Autor:
Fang, Xinran, Lei, Chengleyang, Feng, Wei, Chen, Yunfei, Xiao, Ming, Ge, Ning, Wang, Chengxiang
Rapid advancements in field robots have brought a new kind of cyber physical system (CPS)--unmanned robotic system--under the spotlight. In the upcoming sixth-generation (6G) era, these systems hold great potential to replace humans in hazardous task
Externí odkaz:
http://arxiv.org/abs/2410.18382
To accommodate the evolving demands of unmanned operations, the future sixth-generation (6G) network will support not only communication links but also sensing-communication-computing-control ($\mathbf{SC}^3$) loops. In each $\mathbf{SC}^3$ cycle, th
Externí odkaz:
http://arxiv.org/abs/2410.18370
Autor:
Chen, Houlun, Wang, Xin, Chen, Hong, Zhang, Zeyang, Feng, Wei, Huang, Bin, Jia, Jia, Zhu, Wenwu
Existing Video Corpus Moment Retrieval (VCMR) is limited to coarse-grained understanding, which hinders precise video moment localization when given fine-grained queries. In this paper, we propose a more challenging fine-grained VCMR benchmark requir
Externí odkaz:
http://arxiv.org/abs/2410.08593
Open-vocabulary multi-object tracking (OVMOT) represents a critical new challenge involving the detection and tracking of diverse object categories in videos, encompassing both seen categories (base classes) and unseen categories (novel classes). Thi
Externí odkaz:
http://arxiv.org/abs/2410.08529
Large-scale multimodal models have shown excellent performance over a series of tasks powered by the large corpus of paired multimodal training data. Generally, they are always assumed to receive modality-complete inputs. However, this simple assumpt
Externí odkaz:
http://arxiv.org/abs/2410.06558
Autor:
Liang, Wanchao, Liu, Tianyu, Wright, Less, Constable, Will, Gu, Andrew, Huang, Chien-Chin, Zhang, Iris, Feng, Wei, Huang, Howard, Wang, Junjie, Purandare, Sanket, Nadathur, Gokul, Idreos, Stratos
The development of large language models (LLMs) has been instrumental in advancing state-of-the-art natural language processing applications. Training LLMs with billions of parameters and trillions of tokens require sophisticated distributed systems
Externí odkaz:
http://arxiv.org/abs/2410.06511