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。主题：3D Generation from Unstructured Single-view Data 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
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
Talk·预习资料
https://nvlabs.github.io/eg3d/media/eg3d.pdf
paper链接：
https://arxiv.org/abs/2301.07702https://arxiv.org/abs/2303.01416
paper链接：
https://arxiv.org/abs/2212.11984
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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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