Zobrazeno 1 - 10
of 491
pro vyhledávání: '"Wang, Xiyu"'
Recent advancements in deep learning have yielded promising results for the image shadow removal task. However, most existing methods rely on binary pre-generated shadow masks. The binary nature of such masks could potentially lead to artifacts near
Externí odkaz:
http://arxiv.org/abs/2409.07041
Diffusion-based models for story visualization have shown promise in generating content-coherent images for storytelling tasks. However, how to effectively integrate new characters into existing narratives while maintaining character consistency rema
Externí odkaz:
http://arxiv.org/abs/2405.11852
Autor:
Ndiaye, Papis, Phan-Huy, Dinh-Thuy, Hassan, Ayman, Liao, Jingyi, Wang, Xiyu, Ruttik, Kalle, Jantti, Riku
Ambient backscatter communication technology (AmBC) and a novel device category called zero-energy devices (ZED) have recently emerged as potential components for the forthcoming 6th generation (6G) networks. A ZED communicates with a smartphone with
Externí odkaz:
http://arxiv.org/abs/2309.15040
Diffusion Probabilistic Models (DPMs) have demonstrated substantial promise in image generation tasks but heavily rely on the availability of large amounts of training data. Previous works, like GANs, have tackled the limited data problem by transfer
Externí odkaz:
http://arxiv.org/abs/2308.11948
Diffusion probabilistic models (DPMs) have been shown to generate high-quality images without the need for delicate adversarial training. However, the current sampling process in DPMs is prone to violent shaking. In this paper, we present a novel rev
Externí odkaz:
http://arxiv.org/abs/2308.11941
Autor:
Wang, Dongbo, Liu, Chang, Zhao, Zhixiao, Shen, Si, Liu, Liu, Li, Bin, Hu, Haotian, Wu, Mengcheng, Lin, Litao, Zhao, Xue, Wang, Xiyu
In the context of the rapid development of large language models, we have meticulously trained and introduced the GujiBERT and GujiGPT language models, which are foundational models specifically designed for intelligent information processing of anci
Externí odkaz:
http://arxiv.org/abs/2307.05354
Autor:
Qiu, Zhongwei, Yang, Qiansheng, Wang, Jian, Wang, Xiyu, Xu, Chang, Fu, Dongmei, Yao, Kun, Han, Junyu, Ding, Errui, Wang, Jingdong
One of the mainstream schemes for 2D human pose estimation (HPE) is learning keypoints heatmaps by a neural network. Existing methods typically improve the quality of heatmaps by customized architectures, such as high-resolution representation and vi
Externí odkaz:
http://arxiv.org/abs/2306.17074
Confidence Attention and Generalization Enhanced Distillation for Continuous Video Domain Adaptation
Continuous Video Domain Adaptation (CVDA) is a scenario where a source model is required to adapt to a series of individually available changing target domains continuously without source data or target supervision. It has wide applications, such as
Externí odkaz:
http://arxiv.org/abs/2303.10452
Long Term Evolution (LTE) signal is ubiquitously present in electromagnetic (EM) background environment, which make it an attractive signal source for the ambient backscatter communications (AmBC). In this paper, we propose a system, in which a backs
Externí odkaz:
http://arxiv.org/abs/2301.13664
Autor:
Pang, Pu, Deng, Gang, Bai, Kaihao, Chen, Quan, Sun, Shixuan, Liu, Bo, Xu, Yu, Yao, Hongbo, Wang, Zhengheng, Wang, Xiyu, Liu, Zheng, Song, Zhuo, Yang, Yong, Ma, Tao, Guo, Minyi
In-memory key-value stores (IMKVSes) serve many online applications because of their efficiency. To support data backup, popular industrial IMKVSes periodically take a point-in-time snapshot of the in-memory data with the system call fork. However, t
Externí odkaz:
http://arxiv.org/abs/2301.05861