NIPS Proceedingsβ

Bill Freeman

9 Papers

  • Learning to See Physics via Visual De-animation (2017)
  • MarrNet: 3D Shape Reconstruction via 2.5D Sketches (2017)
  • Shape and Material from Sound (2017)
  • Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling (2016)
  • Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks (2016)
  • Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning (2015)
  • Shape and Illumination from Shading using the Generic Viewpoint Assumption (2014)
  • Nonparametric Bayesian Texture Learning and Synthesis (2009)
  • Segmenting Scenes by Matching Image Composites (2009)