Arxiv paper – HunyuanVideo: A Systematic Framework For Large Video Generative Models

In this episode, we discuss HunyuanVideo: A Systematic Framework For Large Video Generative Models by Weijie Kong, Qi Tian, Zijian Zhang, Rox Min, Zuozhuo Dai, Jin Zhou, Jiangfeng Xiong, Xin Li, Bo Wu, Jianwei Zhang, Kathrina Wu, Qin Lin, Junkun Yuan, Yanxin Long, Aladdin Wang, Andong Wang, Changlin Li, Duojun Huang, Fang Yang, Hao Tan, Hongmei Wang, Jacob Song, Jiawang Bai, Jianbing Wu, Jinbao Xue, Joey Wang, Kai Wang, Mengyang Liu, Pengyu Li, Shuai Li, Weiyan Wang, Wenqing Yu, Xinchi Deng, Yang Li, Yi Chen, Yutao Cui, Yuanbo Peng, Zhentao Yu, Zhiyu He, Zhiyong Xu, Zixiang Zhou, Zunnan Xu, Yangyu Tao, Qinglin Lu, Songtao Liu, Dax Zhou, Hongfa Wang, Yong Yang, Di Wang, Yuhong Liu, Jie Jiang, Caesar Zhong. HunyuanVideo is an innovative open-source video generation model that matches or exceeds the performance of leading closed-source alternatives. It leverages a comprehensive framework encompassing data curation, advanced architecture, progressive scaling, and efficient infrastructure to train a 13-billion-parameter model, the largest of its kind in the open-source domain. Extensive evaluations reveal that HunyuanVideo delivers superior visual quality, motion dynamics, and text-video alignment, and its publicly available code aims to bridge the gap between closed and open-source communities, fostering a more dynamic video generation ecosystem.