One new paper conditionally accepted to SIGGRAPH 2021!
Xianghao Xu's paper (with Autodesk research) on inferring CAD modeling sequences was accepted to CVPR 2021.
Do you work in deep learning? Like Billy Joel songs? Check out the end-of-semester song from Brown's deep learning course.
Applications are now open for our new exploreCSR program, Socially-Responsible AI for Computational Creativity! Learn more here.
Two new papers accepted to 3DV 2020!
Attending SIGGRAPH 2020? Drop by our BoF (Birds of a Feather) session Monday 8/24 at 11am Pacific Time to discuss the future of synthetic 3D indoor scene datasets.
New paper accepted to SIGGRAPH Asia 2020! "ShapeAssembly: Learning to Generate Programs for 3D Shape Structure Synthesis."
Wallace Lira's work on image-to-image translation via multiple small "hops" has been accepted to ECCV 2020.
The new Brown Visual Computing website is live! There are a couple of 'graphics-y' easter eggs on the page--see if you can find them 😉
Won an NSF CAREER Award for work on Learning Neurosymbolic 3D Models.
My PhD advisor, Pat Hanrahan, won a Turing Award!
Check out our new state-of-the-art report (to be presented at Eurographics 2020) on Learning Generative Models of 3D Structures.
Paper on graph-based generative models for indoor scenes accepted to SIGGRAPH 2019.
New paper on a faster image-based generative model for indoor scenes accepted to CVPR 2019.
I'll be presenting a tutorial on Learning Generative Models of 3D Structures at Eurographics 2019.
I'm co-organizing a workshop on 3D Scene Generation at CVPR 2019.
Yunchao Liu's work on inferring scene-generating programs from images accepted to ICLR 2019.
Kevin Ellis's work on visual program induction from hand-drawn graph sketches accepted as a spotlight presentation at NeurIPS 2018.
Aaron Gokaslan and Vivek Ramanujan's work on unsupervised image translation with large shape deformation to be presented at ECCV 2018.
New paper on deep convolutional scene synthesis models accepted to SIGGRAPH 2018.
Angela Dai's work on large-scale 3D scan completion accepted to CVPR 2018.
New paper on learning procedural models from examples accepted to Eurographics 2018.
Maxime Voisin's work on improved training for neural autoregressive data completion models accepted to the NIPS 2017 Bayesian Deep Learning Workshop.
New post about an algorithm for writing research papers.
Moved to Brown!
Interview about Neurally-Guided Procedural Models on the AI Guild podcast.
Posted tech report on deep amortized inference for probabilistic programs.
Neurally-Guided Procedural Models paper accepted to NIPS 2016.