Zobrazeno 1 - 10
of 20 357
pro vyhledávání: '"YANG, FENG"'
The application of vision-based multi-view environmental perception system has been increasingly recognized in autonomous driving technology, especially the BEV-based models. Current state-of-the-art solutions primarily encode image features from eac
Externí odkaz:
http://arxiv.org/abs/2412.18884
Rapid advancements in generative models have made it possible to create hyper-realistic videos. As their applicability increases, their unauthorized use has raised significant concerns, leading to the growing demand for techniques to protect the owne
Externí odkaz:
http://arxiv.org/abs/2412.09122
Autor:
Xu, Jiahua, Zhou, Dawei, Hu, Lei, Guo, Jianfeng, Yang, Feng, Liu, Zaiyi, Wang, Nannan, Gao, Xinbo
Motion artifacts present in magnetic resonance imaging (MRI) can seriously interfere with clinical diagnosis. Removing motion artifacts is a straightforward solution and has been extensively studied. However, paired data are still heavily relied on i
Externí odkaz:
http://arxiv.org/abs/2412.07590
Transformer-based multi-object tracking (MOT) methods have captured the attention of many researchers in recent years. However, these models often suffer from slow inference speeds due to their structure or other issues. To address this problem, we r
Externí odkaz:
http://arxiv.org/abs/2411.15811
In conventional electrides, excess electrons are localized in crystal voids to serve as anions. Most of these electrides are metallic and the metal cations are primarily from the s-block, d-block, or rare-earth elements. Here, we report a class of p-
Externí odkaz:
http://arxiv.org/abs/2411.12170
Multi-object tracking is advancing through two dominant paradigms: traditional tracking by detection and newly emerging tracking by query. In this work, we fuse them together and propose the tracking-by-detection-and-query paradigm, which is achieved
Externí odkaz:
http://arxiv.org/abs/2411.06197
Autor:
Zhang, Shu, Pang, Jinbo, Li, Yufen, Yang, Feng, Gemming, Thomas, Wang, Kai, Wang, Xiao, Peng, Songang, Liu, Xiaoyan, Chang, Bin, Liu, Hong, Zhou, Weijia, Cuniberti, Gianaurelio, Rümmeli, Mark H.
Carbon nanotubes (CNTs) have attracted great attentions in the field of electronics, sensors, healthcare, and energy conversion. Such emerging applications have driven the carbon nanotube research in a rapid fashion. Indeed, the structure control ove
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A89410
https://tud.qucosa.de/api/qucosa%3A89410/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A89410/attachment/ATT-0/
As 3D Gaussian Splatting~(3D-GS) gains significant attention and its commercial usage increases, the need for watermarking technologies to prevent unauthorized use of the 3D-GS models and rendered images has become increasingly important. In this pap
Externí odkaz:
http://arxiv.org/abs/2409.13222
Autor:
Tan, Zhuolin, Gao, Chenqiang, Qin, Anyong, Chen, Ruixin, Song, Tiecheng, Yang, Feng, Meng, Deyu
Analyzing student actions is an important and challenging task in educational research. Existing efforts have been hampered by the lack of accessible datasets to capture the nuanced action dynamics in classrooms. In this paper, we present a new multi
Externí odkaz:
http://arxiv.org/abs/2409.00926
Autor:
Lee, Seung Hyun, Ke, Junjie, Li, Yinxiao, He, Junfeng, Hickson, Steven, Datsenko, Katie, Kim, Sangpil, Yang, Ming-Hsuan, Essa, Irfan, Yang, Feng
The goal of image cropping is to identify visually appealing crops within an image. Conventional methods rely on specialized architectures trained on specific datasets, which struggle to be adapted to new requirements. Recent breakthroughs in large v
Externí odkaz:
http://arxiv.org/abs/2408.07790