Zobrazeno 1 - 10
of 1 592
pro vyhledávání: '"Pan, Xiang"'
Autor:
Wu, Shengmiao, Shi, Xiheng, Kalita, Nibedita, Pan, Xiang, Tian, Qiguo, Ji, Tuo, Zhang, Shaohua, Dai, Xuejie, Jiang, Peng, Yang, Chenwei, Zhou, Hongyan
SDSS J083942.11+380526.3 ($z=2.315$) is a FeLoBAL quasar that exhibits visible Balmer absorption lines (H$\alpha$), implying a significant $n=2$ population. The quasar also shows an array of absorption lines, including \oi, \niii, \feii, \mgii, \alii
Externí odkaz:
http://arxiv.org/abs/2407.17116
We revisit data selection in a modern context of finetuning from a fundamental perspective. Extending the classical wisdom of variance minimization in low dimensions to high-dimensional finetuning, our generalization analysis unveils the importance o
Externí odkaz:
http://arxiv.org/abs/2407.06120
Autor:
Conde, Marcos V., Zadtootaghaj, Saman, Barman, Nabajeet, Timofte, Radu, He, Chenlong, Zheng, Qi, Zhu, Ruoxi, Tu, Zhengzhong, Wang, Haiqiang, Chen, Xiangguang, Meng, Wenhui, Pan, Xiang, Shi, Huiying, Zhu, Han, Xu, Xiaozhong, Sun, Lei, Chen, Zhenzhong, Liu, Shan, Zhang, Zicheng, Wu, Haoning, Zhou, Yingjie, Li, Chunyi, Liu, Xiaohong, Lin, Weisi, Zhai, Guangtao, Sun, Wei, Cao, Yuqin, Jiang, Yanwei, Jia, Jun, Zhang, Zhichao, Chen, Zijian, Zhang, Weixia, Min, Xiongkuo, Göring, Steve, Qi, Zihao, Feng, Chen
This paper reviews the AIS 2024 Video Quality Assessment (VQA) Challenge, focused on User-Generated Content (UGC). The aim of this challenge is to gather deep learning-based methods capable of estimating the perceptual quality of UGC videos. The user
Externí odkaz:
http://arxiv.org/abs/2404.16205
Autor:
Li, Xin, Yuan, Kun, Pei, Yajing, Lu, Yiting, Sun, Ming, Zhou, Chao, Chen, Zhibo, Timofte, Radu, Sun, Wei, Wu, Haoning, Zhang, Zicheng, Jia, Jun, Zhang, Zhichao, Cao, Linhan, Chen, Qiubo, Min, Xiongkuo, Lin, Weisi, Zhai, Guangtao, Sun, Jianhui, Wang, Tianyi, Li, Lei, Kong, Han, Wang, Wenxuan, Li, Bing, Luo, Cheng, Wang, Haiqiang, Chen, Xiangguang, Meng, Wenhui, Pan, Xiang, Shi, Huiying, Zhu, Han, Xu, Xiaozhong, Sun, Lei, Chen, Zhenzhong, Liu, Shan, Kong, Fangyuan, Fan, Haotian, Xu, Yifang, Xu, Haoran, Yang, Mengduo, Zhou, Jie, Li, Jiaze, Wen, Shijie, Xu, Mai, Li, Da, Yao, Shunyu, Du, Jiazhi, Zuo, Wangmeng, Li, Zhibo, He, Shuai, Ming, Anlong, Fu, Huiyuan, Ma, Huadong, Wu, Yong, Xue, Fie, Zhao, Guozhi, Du, Lina, Guo, Jie, Zhang, Yu, Zheng, Huimin, Chen, Junhao, Liu, Yue, Zhou, Dulan, Xu, Kele, Xu, Qisheng, Sun, Tao, Ding, Zhixiang, Hu, Yuhang
This paper reviews the NTIRE 2024 Challenge on Shortform UGC Video Quality Assessment (S-UGC VQA), where various excellent solutions are submitted and evaluated on the collected dataset KVQ from popular short-form video platform, i.e., Kuaishou/Kwai
Externí odkaz:
http://arxiv.org/abs/2404.11313
Multi-source domain adaptation aims to reduce performance degradation when applying machine learning models to unseen domains. A fundamental challenge is devising the optimal strategy for feature selection. Existing literature is somewhat paradoxical
Externí odkaz:
http://arxiv.org/abs/2403.06424
Let $G=(V(G),E(G))$ be a graph with vertex set $V(G)$ and edge set $E(G)$. The resistance distance $R_G(x,y)$ between two vertices $x,y$ of $G$ is defined to be the effective resistance between the two vertices in the corresponding electrical network
Externí odkaz:
http://arxiv.org/abs/2403.06096
Adversarial attacks can readily disrupt the image classification system, revealing the vulnerability of DNN-based recognition tasks. While existing adversarial perturbations are primarily applied to uncompressed images or compressed images by the tra
Externí odkaz:
http://arxiv.org/abs/2401.03115
Accurate precipitation forecasting is a vital challenge of both scientific and societal importance. Data-driven approaches have emerged as a widely used solution for addressing this challenge. However, solely relying on data-driven approaches has lim
Externí odkaz:
http://arxiv.org/abs/2310.02676
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Constructing atom-pair engineering and improving the activity of metal single-atom nanozyme (SAzyme) is significant but challenging. Herein, we design the atom-pair engineering of Zn-SA/CNCl SAzyme by simultaneously constructing Zn-N4 sites
Externí odkaz:
https://doaj.org/article/f01aec57f22643d2b3df0b7761099c29
Learned Image Compression (LIC) has recently become the trending technique for image transmission due to its notable performance. Despite its popularity, the robustness of LIC with respect to the quality of image reconstruction remains under-explored
Externí odkaz:
http://arxiv.org/abs/2306.01125