Talk预告 | 香港中文大学博士生徐英豪：从不规则的单目图片数据构建3D生成模型

本期为TechBeat人工智能社区第498期线上Talk！

北京时间5月18日(周四)20:00，香港中文大学博士生 — 徐英豪的Talk将准时在TechBeat人工智能社区开播！他与大家分享的主题是: “3D Generation from Unstructured Single-view Data ”，届时将介绍和探讨3d场景生成模型的标注与生成。

Talk·信息

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主题：3D Generation from Unstructured Single-view Data 

嘉宾：香港中文大学 博士生 —徐英豪

时间：北京时间 5月18日 (周四) 20:00

地点：TechBeat人工智能社区

http://www.techbeat.net/

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Talk·介绍

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Pixel-based content creation has made remarkable progress thanks to 2D generative models. However, a deeper understanding of the 3D world beyond image space is necessary for a wide range of real-world applications, such as AR and VR. Traditional 3D content creation authoring pipelines require professional expertise and significant financial investment to build large 3D datasets. In this talk, I will introduce our recent works in enabling 3D generative modeling from unstructured 2D images, especially in single-view data, by introducing powerful and effective 3D representations. It paves the way for generating high-quality 3D assets efficiently. Additionally, we also generalize the 3D generative model to in-the-wild objects and complex scenes, enabling 3D image generation on ImageNet and controllable 3D scene synthesis. These efforts are integral to our long-term vision of enabling high-quality, user-friendly 3D content creation for a broad audience

Talk大纲

1、如何让3d生成模型摆脱对相机标注的依赖

2、在大规模复杂数据集例如imagenet上构建高质量的3d生成模型

3、不规则场景数据集构建可控的3d场景生成模型

Talk·预习资料

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paper链接：

https://nvlabs.github.io/eg3d/media/eg3d.pdf

paper链接：

https://arxiv.org/abs/2301.07702

paper链接：

https://arxiv.org/abs/2303.01416

paper链接：

https://arxiv.org/abs/2212.11984

Talk·提问交流

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Talk·嘉宾介绍▼

徐英豪

香港中文大学 博士生

Yinghao Xu is a final-year Ph.D. student at Multimedia Lab (MMLab), Department of Information Engineering in The Chinese University of Hong Kong. His supervisor are Prof. Dahua Lin and Prof. Bolei Zhou. He is very interested in generative models and neural rendering, particularly in 3D generative models. During his Ph.D., he is fortunate to visit Stanford computational group, working with Prof. Gordon Wetzstein. Many of his papers have been awarded as oral representation and best paper candidate at CVPR, ECCV, NeurIPS and ICLR.

Github：

https://justimyhxu.github.io/

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