G
Gordon Wetzstein
Researcher at Stanford University
Publications - 306
Citations - 16177
Gordon Wetzstein is an academic researcher from Stanford University. The author has contributed to research in topics: Computer science & Computational photography. The author has an hindex of 51, co-authored 258 publications receiving 9793 citations. Previous affiliations of Gordon Wetzstein include Bauhaus University, Weimar & University of British Columbia.
Papers
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Proceedings Article
Implicit Neural Representations with Periodic Activation Functions
TL;DR: In this paper, the authors propose to leverage periodic activation functions for implicit neural representations and demonstrate that these networks, dubbed sinusoidal representation networks or Sirens, are ideally suited for representing complex natural signals and their derivatives.
Proceedings Article
Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
TL;DR: The proposed Scene Representation Networks (SRNs), a continuous, 3D-structure-aware scene representation that encodes both geometry and appearance, are demonstrated by evaluating them for novel view synthesis, few-shot reconstruction, joint shape and appearance interpolation, and unsupervised discovery of a non-rigid face model.
Journal ArticleDOI
Simultaneous whole-animal 3D imaging of neuronal activity using light-field microscopy
Robert Prevedel,Young-Gyu Yoon,Maximilian Hoffmann,Maximilian Hoffmann,Maximilian Hoffmann,Nikita Pak,Gordon Wetzstein,Saul Kato,Tina Schrödel,Ramesh Raskar,Manuel Zimmer,Edward S. Boyden,Alipasha Vaziri,Alipasha Vaziri,Alipasha Vaziri +14 more
TL;DR: This work demonstrates simultaneous functional imaging of neuronal activity at single-neuron resolution in an entire Caenorhabditis elegans and in larval zebrafish brain with high-speed volumetric calcium imaging.
Journal ArticleDOI
Tensor displays: compressive light field synthesis using multilayer displays with directional backlighting
TL;DR: A unified optimization framework, based on nonnegative tensor factorization (NTF), encompassing all tensor display architectures is introduced, which is the first to allow joint multilayer, multiframe light field decompositions and is also the first optimization method for designs combining multiple layers with directional backlighting.
Journal ArticleDOI
Inference in artificial intelligence with deep optics and photonics.
Gordon Wetzstein,Aydogan Ozcan,Sylvain Gigan,Shanhui Fan,Dirk Englund,Marin Soljacic,Cornelia Denz,David A. B. Miller,Demetri Psaltis +8 more
TL;DR: Recent work on optical computing for artificial intelligence applications is reviewed and its promise and challenges are discussed.