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12月18日 陈昕苑：基于扩散模型的大规模生成式视频生成模型
- 来源：
- 学校官网
- 收录时间：
- 2024-12-13 09:09:25
- 时间：
- 2024-12-18 15:00:00
- 地点：
- 闵行校区信息楼魔方厅
- 报告人：
- 陈昕苑
- 学校：
- -/-
- 关键词：
- diffusion models, video generation, Sora, generative models, generative adversarial networks, high-definition videos, text-to-video
- 简介：
- As OpenAI introduces Sora, a generative text-to-video diffusion model, it opens the door to generation of high-definition videos at the minute level from text descriptions. This groundbreaking model not only showcases the vast potential of video generation but also captures the attention of researchers and enthusiasts alike. In this talk, we will delve into the evolutionary path of large-scale video generation models and explore key research milestones. We will then analyze the technical advancements and breakthrough effects achieved by the Sora model. However, while the success of Sora, there still exist limitations and bottlenecks in video generation. Concluding the talk, we will discuss the challenges faced in video generation and explore potential avenues for future breakthroughs.
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报告介绍：
As OpenAI introduces Sora, a generative text-to-video diffusion model, it opens the door to generation of high-definition videos at the minute level from text descriptions. This groundbreaking model not only showcases the vast potential of video generation but also captures the attention of researchers and enthusiasts alike. In this talk, we will delve into the evolutionary path of large-scale video generation models and explore key research milestones. We will then analyze the technical advancements and breakthrough effects achieved by the Sora model. However, while the success of Sora, there still exist limitations and bottlenecks in video generation. Concluding the talk, we will discuss the challenges faced in video generation and explore potential avenues for future breakthroughs.
报告人介绍：
Dr. Xinyuan Chen is currently a researcher at the Shanghai Artificial Intelligence Lab, collaborating closely with Prof. Yu Qiao. During 2020-2022, she did her post-doc research at East China Normal University, supervised by Prof. Yue Lu. In 2020, she completed her dual PhD from Shanghai Jiao Tong University and the University of Technology Sydney, under the supervision of Prof. Xiaokang Yang and Prof. Dacheng Tao. Her research interests lie in generative models, diffusion models, and generative adversarial networks. Currently, she focuses her work on image and video generation, large-scale video generation models, as well as controllable generation incorporating multi-modality and semantic conditions.
