Zobrazeno 1 - 10
of 426 682
pro vyhledávání: '"Bin, P."'
Autor:
Pang, Yatian, Jin, Peng, Yang, Shuo, Lin, Bin, Zhu, Bin, Tang, Zhenyu, Chen, Liuhan, Tay, Francis E. H., Lim, Ser-Nam, Yang, Harry, Yuan, Li
Autoregressive models, built based on the Next Token Prediction (NTP) paradigm, show great potential in developing a unified framework that integrates both language and vision tasks. In this work, we rethink the NTP for autoregressive image generatio
Externí odkaz:
http://arxiv.org/abs/2412.15321
Autor:
Pang, Yatian, Zhu, Bin, Lin, Bin, Zheng, Mingzhe, Tay, Francis E. H., Lim, Ser-Nam, Yang, Harry, Yuan, Li
In this work, we present DreamDance, a novel method for animating human images using only skeleton pose sequences as conditional inputs. Existing approaches struggle with generating coherent, high-quality content in an efficient and user-friendly man
Externí odkaz:
http://arxiv.org/abs/2412.00397
Autor:
Lin, Bin, Ge, Yunyang, Cheng, Xinhua, Li, Zongjian, Zhu, Bin, Wang, Shaodong, He, Xianyi, Ye, Yang, Yuan, Shenghai, Chen, Liuhan, Jia, Tanghui, Zhang, Junwu, Tang, Zhenyu, Pang, Yatian, She, Bin, Yan, Cen, Hu, Zhiheng, Dong, Xiaoyi, Chen, Lin, Pan, Zhang, Zhou, Xing, Dong, Shaoling, Tian, Yonghong, Yuan, Li
We introduce Open-Sora Plan, an open-source project that aims to contribute a large generation model for generating desired high-resolution videos with long durations based on various user inputs. Our project comprises multiple components for the ent
Externí odkaz:
http://arxiv.org/abs/2412.00131
Autor:
Xu, Ronghui, Cheng, Hanyin, Guo, Chenjuan, Gao, Hongfan, Hu, Jilin, Yang, Sean Bin, Yang, Bin
Developing effective path representations has become increasingly essential across various fields within intelligent transportation. Although pre-trained path representation learning models have shown improved performance, they predominantly focus on
Externí odkaz:
http://arxiv.org/abs/2411.18428
Autor:
Hsu, Aliyah R., Zhu, James, Wang, Zhichao, Bi, Bin, Mehrotra, Shubham, Pentyala, Shiva K., Tan, Katherine, Mao, Xiang-Bo, Omrani, Roshanak, Chaudhuri, Sougata, Radhakrishnan, Regunathan, Asur, Sitaram, Cheng, Claire Na, Yu, Bin
LLMs have demonstrated impressive proficiency in generating coherent and high-quality text, making them valuable across a range of text-generation tasks. However, rigorous evaluation of this generated content is crucial, as ensuring its quality remai
Externí odkaz:
http://arxiv.org/abs/2411.02448
Precise alignment of multi-modal images with inherent feature discrepancies poses a pivotal challenge in deformable image registration. Traditional learning-based approaches often consider registration networks as black boxes without interpretability
Externí odkaz:
http://arxiv.org/abs/2411.01399
Migrating Fortran code to C++ is a common task for many scientific computing teams, driven by the need to leverage modern programming paradigms, enhance cross-platform compatibility, and improve maintainability. Automating this translation process us
Externí odkaz:
http://arxiv.org/abs/2412.19770
Recently, Hadfield et al. proposed the quantum alternating operator ansatz algorithm (QAOA+), an extension of the quantum approximate optimization algorithm (QAOA), to solve constrained combinatorial optimization problems (CCOPs). Compared with QAOA,
Externí odkaz:
http://arxiv.org/abs/2412.19621
According to the Schr\"odinger-Poisson (SP) equations, fuzzy dark matter (FDM) can form a stable equilibrium configuration, the so-called FDM soliton. The SP system can also determine the evolution of FDM solitons, such as head-on collision. In this
Externí odkaz:
http://arxiv.org/abs/2412.19262
Pre-trained model assessment for transfer learning aims to identify the optimal candidate for the downstream tasks from a model hub, without the need of time-consuming fine-tuning. Existing advanced works mainly focus on analyzing the intrinsic chara
Externí odkaz:
http://arxiv.org/abs/2412.19085