Zobrazeno 1 - 10
of 44 201
pro vyhledávání: '"An, Zeyu"'
Representation learning on text-attributed graphs (TAGs) has attracted significant interest due to its wide-ranging real-world applications, particularly through Graph Neural Networks (GNNs). Traditional GNN methods focus on encoding the structural i
Externí odkaz:
http://arxiv.org/abs/2410.01457
Non-semantic features or semantic-agnostic features, which are irrelevant to image context but sensitive to image manipulations, are recognized as evidential to Image Manipulation Localization (IML). Since manual labels are impossible, existing works
Externí odkaz:
http://arxiv.org/abs/2412.14598
Autor:
Lu, Shunlin, Wang, Jingbo, Lu, Zeyu, Chen, Ling-Hao, Dai, Wenxun, Dong, Junting, Dou, Zhiyang, Dai, Bo, Zhang, Ruimao
The scaling law has been validated in various domains, such as natural language processing (NLP) and massive computer vision tasks; however, its application to motion generation remains largely unexplored. In this paper, we introduce a scalable motio
Externí odkaz:
http://arxiv.org/abs/2412.14559
Numerous remarkable advancements have been made in accuracy, speed, and parallelism for solving the Unmanned Aerial Vehicle Route Planing (UAVRP). However, existing UAVRP solvers face challenges when attempting to scale effectively and efficiently fo
Externí odkaz:
http://arxiv.org/abs/2412.15537
Autor:
Qwen, Yang, An, Yang, Baosong, Zhang, Beichen, Hui, Binyuan, Zheng, Bo, Yu, Bowen, Li, Chengyuan, Liu, Dayiheng, Huang, Fei, Wei, Haoran, Lin, Huan, Yang, Jian, Tu, Jianhong, Zhang, Jianwei, Yang, Jianxin, Yang, Jiaxi, Zhou, Jingren, Lin, Junyang, Dang, Kai, Lu, Keming, Bao, Keqin, Yang, Kexin, Yu, Le, Li, Mei, Xue, Mingfeng, Zhang, Pei, Zhu, Qin, Men, Rui, Lin, Runji, Li, Tianhao, Xia, Tingyu, Ren, Xingzhang, Ren, Xuancheng, Fan, Yang, Su, Yang, Zhang, Yichang, Wan, Yu, Liu, Yuqiong, Cui, Zeyu, Zhang, Zhenru, Qiu, Zihan
In this report, we introduce Qwen2.5, a comprehensive series of large language models (LLMs) designed to meet diverse needs. Compared to previous iterations, Qwen 2.5 has been significantly improved during both the pre-training and post-training stag
Externí odkaz:
http://arxiv.org/abs/2412.15115
Autor:
Wang, Fu, Zhang, Yanghao, Yin, Xiangyu, Cheng, Guangliang, Fu, Zeyu, Huang, Xiaowei, Ruan, Wenjie
Camera-based Bird's Eye View (BEV) perception models receive increasing attention for their crucial role in autonomous driving, a domain where concerns about the robustness and reliability of deep learning have been raised. While only a few works hav
Externí odkaz:
http://arxiv.org/abs/2412.13913
Autor:
Wu, Kun, Hou, Chengkai, Liu, Jiaming, Che, Zhengping, Ju, Xiaozhu, Yang, Zhuqin, Li, Meng, Zhao, Yinuo, Xu, Zhiyuan, Yang, Guang, Zhao, Zhen, Li, Guangyu, Jin, Zhao, Wang, Lecheng, Mao, Jilei, Wang, Xinhua, Fan, Shichao, Liu, Ning, Ren, Pei, Zhang, Qiang, Lyu, Yaoxu, Liu, Mengzhen, He, Jingyang, Luo, Yulin, Gao, Zeyu, Li, Chenxuan, Gu, Chenyang, Fu, Yankai, Wu, Di, Wang, Xingyu, Chen, Sixiang, Wang, Zhenyu, An, Pengju, Qian, Siyuan, Zhang, Shanghang, Tang, Jian
Developing robust and general-purpose robotic manipulation policies is a key goal in the field of robotics. To achieve effective generalization, it is essential to construct comprehensive datasets that encompass a large number of demonstration trajec
Externí odkaz:
http://arxiv.org/abs/2412.13877
Autor:
Zhu, Xuekang, Ma, Xiaochen, Su, Lei, Jiang, Zhuohang, Du, Bo, Wang, Xiwen, Lei, Zeyu, Feng, Wentao, Pun, Chi-Man, Zhou, Jizhe
The mesoscopic level serves as a bridge between the macroscopic and microscopic worlds, addressing gaps overlooked by both. Image manipulation localization (IML), a crucial technique to pursue truth from fake images, has long relied on low-level (mic
Externí odkaz:
http://arxiv.org/abs/2412.13753
Autor:
Yang, Jian, Zhang, Jiajun, Yang, Jiaxi, Jin, Ke, Zhang, Lei, Peng, Qiyao, Deng, Ken, Miao, Yibo, Liu, Tianyu, Cui, Zeyu, Hui, Binyuan, Lin, Junyang
Code completion has become an essential tool for daily software development. Existing evaluation benchmarks often employ static methods that do not fully capture the dynamic nature of real-world coding environments and face significant challenges, in
Externí odkaz:
http://arxiv.org/abs/2412.11990
While haircut indicates distinct personality, existing avatar generation methods fail to model practical hair due to the general or entangled representation. We propose StrandHead, a novel text to 3D head avatar generation method capable of generatin
Externí odkaz:
http://arxiv.org/abs/2412.11586