no code implementations • 1 Sep 2023 • Xin Li, Wenqing Chu, Ye Wu, Weihang Yuan, Fanglong Liu, Qi Zhang, Fu Li, Haocheng Feng, Errui Ding, Jingdong Wang
In this paper, we present VideoGen, a text-to-video generation approach, which can generate a high-definition video with high frame fidelity and strong temporal consistency using reference-guided latent diffusion.
3 code implementations • 23 Aug 2022 • Ren Yang, Radu Timofte, Qi Zhang, Lin Zhang, Fanglong Liu, Dongliang He, Fu Li, He Zheng, Weihang Yuan, Pavel Ostyakov, Dmitry Vyal, Magauiya Zhussip, Xueyi Zou, Youliang Yan, Lei LI, Jingzhu Tang, Ming Chen, Shijie Zhao, Yu Zhu, Xiaoran Qin, Chenghua Li, Cong Leng, Jian Cheng, Claudio Rota, Marco Buzzelli, Simone Bianco, Raimondo Schettini, Dafeng Zhang, Feiyu Huang, Shizhuo Liu, Xiaobing Wang, Zhezhu Jin, Bingchen Li, Xin Li, Mingxi Li, Ding Liu, Wenbin Zou, Peijie Dong, Tian Ye, Yunchen Zhang, Ming Tan, Xin Niu, Mustafa Ayazoglu, Marcos Conde, Ui-Jin Choi, Zhuang Jia, Tianyu Xu, Yijian Zhang, Mao Ye, Dengyan Luo, Xiaofeng Pan, Liuhan Peng
The homepage of this challenge is at https://github. com/RenYang-home/AIM22_CompressSR.
no code implementations • 9 Feb 2022 • Weihang Yuan, Hector Munoz-Avila, Venkatsampath Raja Gogineni, Sravya Kondrakunta, Michael Cox, Lifang He
The ability of an agent to change its objectives in response to unexpected events is desirable in dynamic environments.
no code implementations • 21 Jun 2020 • Weihang Yuan, Héctor Muñoz-Avila
Hierarchical DQN (h-DQN) is a two-level architecture of feedforward neural networks where the meta level selects goals and the lower level takes actions to achieve the goals.
Hierarchical Reinforcement Learning
reinforcement-learning
+2
no code implementations • 20 Sep 2019 • Hossein K. Mousavi, Guangyi Liu, Weihang Yuan, Martin Takáč, Héctor Muñoz-Avila, Nader Motee
We propose a planning and perception mechanism for a robot (agent), that can only observe the underlying environment partially, in order to solve an image classification problem.