| A Bayes-Optimal View on Adversarial Examples | 0 | 0.34 | 2021 |
| Understanding and Simplifying Perceptual Distances | 0 | 0.34 | 2021 |
| The Surprising Effectiveness Of Linear Unsupervised Image-To-Image Translation | 0 | 0.34 | 2020 |
| Special Issue: Advances in Architectures and Theories for Computer Vision. | 0 | 0.34 | 2020 |
| Why do deep convolutional networks generalize so poorly to small image transformations? | 11 | 0.53 | 2018 |
| On GANs and GMMs. | 1 | 0.36 | 2018 |
| Reflection Separation Using Guided Annotation | 1 | 0.35 | 2017 |
| Power-Efficient Cameras Using Natural Image Statistics. | 0 | 0.34 | 2016 |
| Statistics of RGBD Images. | 0 | 0.34 | 2016 |
| Beyond Brightness Constancy: Learning Noise Models for Optical Flow. | 0 | 0.34 | 2016 |
| The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors | 7 | 0.46 | 2015 |
| The Factored Frontier Algorithm for Approximate Inference in DBNs | 33 | 2.49 | 2013 |
| Loopy belief propagation for approximate inference: an empirical study | 586 | 36.39 | 2013 |
| Tighter Linear Program Relaxations for High Order Graphical Models. | 5 | 0.42 | 2013 |
| Learning the Local Statistics of Optical Flow. | 6 | 0.70 | 2013 |
| Globally Optimizing Graph Partitioning Problems Using Message Passing. | 6 | 0.55 | 2012 |
| Multidimensional spectral hashing | 53 | 2.41 | 2012 |
| Convergent message passing algorithms: a unifying view | 52 | 1.83 | 2012 |
| Learning about Canonical Views from Internet Image Collections. | 13 | 0.57 | 2012 |
| "Natural Images, Gaussian Mixtures and Dead Leaves". | 45 | 2.22 | 2012 |
| Globally Optimizing Graph Partitioning Problems Using Message Passing | 0 | 0.34 | 2012 |
| From learning models of natural image patches to whole image restoration | 357 | 9.82 | 2011 |
| Understanding Blind Deconvolution Algorithms | 107 | 2.75 | 2011 |
| Efficient marginal likelihood optimization in blind deconvolution | 222 | 6.02 | 2011 |
| Belief propagation: technical perspective | 0 | 0.34 | 2010 |
| Semantic label sharing for learning with many categories | 59 | 2.09 | 2010 |
| SPRINT: side-chain prediction inference toolbox for multistate protein design. | 4 | 0.52 | 2010 |
| The 'tree-dependent components' of natural scenes are edge filters. | 5 | 0.64 | 2009 |
| Scale invariance and noise in natural images | 42 | 2.44 | 2009 |
| Informative sensing of natural images | 5 | 0.50 | 2009 |
| Semi-Supervised Learning in Gigantic Image Collections | 52 | 4.47 | 2009 |
| Informative Sensing | 1 | 0.36 | 2009 |
| Learning to Combine Bottom-Up and Top-Down Segmentation | 105 | 6.72 | 2009 |
| Understanding and evaluating blind deconvolution algorithms | 378 | 15.43 | 2009 |
| Tightening LP Relaxations for MAP using Message Passing | 135 | 3.99 | 2008 |
| Discrete-Input Two-Dimensional Gaussian Channels With Memory: Estimation and Information Rates Via Graphical Models and Statistical Mechanics | 28 | 1.61 | 2008 |
| A Closed-Form Solution to Natural Image Matting | 688 | 31.57 | 2008 |
| Spectral Hashing | 15 | 4.98 | 2008 |
| Small codes and large image databases for recognition | 392 | 29.90 | 2008 |
| Latent Topic Models for Hypertext | 19 | 1.33 | 2008 |
| Minimizing and learning energy functions for side-chain prediction. | 40 | 2.25 | 2008 |
| Human-assisted motion annotation | 94 | 5.23 | 2008 |
| User assisted separation of reflections from a single image using a sparsity prior. | 110 | 8.68 | 2007 |
| Hidden Topic Markov Models | 135 | 6.23 | 2007 |
| Hidden Topic Markov Models | 0 | 0.34 | 2007 |
| MAP Estimation, Linear Programming and Belief Propagation with Convex Free Energies | 70 | 3.96 | 2007 |
| What Makes A Good Model Of Natural Images? | 84 | 8.93 | 2007 |
| Seamless image stitching by minimizing false edges. | 52 | 3.31 | 2006 |
| Incorporating non-motion cues into 3D motion segmentation | 11 | 0.61 | 2006 |
| Generalized spectral bounds for sparse LDA | 43 | 3.63 | 2006 |
