EI 2024 Plenary 2: Neural Radiance Fields

Описание: This plenary presentation was delivered at the Electronic Imaging Symposium held in Burlingame, CA over 21-25 January 2024. For more information see: http://www.electronicimaging.org

Title: Neural Radiance Fields

Abstract: Neural Radiance Fields (NeRF) model 3D scenes using a combination of deep learning and ray tracing, wherein the color and volumetric density of a scene is encoded within the weights of a neural network. NeRF originally began as a technique for recovering a 3D model of a scene from a set of 2D images, thereby allowing new photorealistic views of that 3D scene to be rendered. But over time, NeRF has evolved into a general purpose framework for parameterizing and optimizing 3D scenes for a wide variety of applications such as computational photography, robotics, inverse rendering, and generative AI (e.g. synthesizing 3D models from text prompts). This talk reviews the basics of NeRF, discuss recent progress in the field, demonstrate a variety of applications that NeRF enables, and speculate upon the impact that this nascent technology may have on imaging and AI in the future.

Speaker: Jon Barron, senior staff research scientist, Google Research (US) (United States)

Biography: Jon Barron is a senior staff research scientist at Google Research in San Francisco, where he works on computer vision and machine learning. He received a PhD in computer science from the University of California, Berkeley, where he was advised by Jitendra Malik. He received a National Science Foundation Graduate Research Fellowship in 2009, the C.V. Ramamoorthy Distinguished Research Award in 2013, and the PAMI Young Researcher Award in 2020. His works have garnered awards at ECCV 2016, TPAMI 2016, ECCV 2020, ICCV 2021, CVPR 2022, the 2022 Communications of the ACM, and ICLR 2023.

© 2024, Society for Imaging Science and Technology (IS&T)