924 citations · 4.1k across the 42 of their papers we have counts for
12 papers · 1 filter
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification
Massimiliano Patacchiola, John Bronskill, Aliaksandra Shysheya +3
Recent years have seen a growth in user-centric applications that require effective knowledge transfer across tasks in the low-data regime. An example is personalization, where a p…
Occupancy Networks: Learning 3D Reconstruction in Function Space
Lars Mescheder, Michael Oechsle, Michael Niemeyer +2
With the advent of deep neural networks, learning-based approaches for 3D reconstruction have gained popularity. However, unlike for images, in 3D there is no canonical representat…
Contextual Face Recognition with a Nested-Hierarchical Nonparametric Identity Model
Daniel C. Castro, Sebastian Nowozin
Current face recognition systems typically operate via classification into known identities obtained from supervised identity annotations. There are two problems with this paradigm…
From Face Recognition to Models of Identity: A Bayesian Approach to Learning about Unknown Identities from Unsupervised Data
Daniel C. Castro, Sebastian Nowozin
Current face recognition systems robustly recognize identities across a wide variety of imaging conditions. In these systems recognition is performed via classification into known…
Deep Directional Statistics: Pose Estimation with Uncertainty Quantification
Sergey Prokudin, Peter Gehler, Sebastian Nowozin
Modern deep learning systems successfully solve many perception tasks such as object pose estimation when the input image is of high quality. However, in challenging imaging condit…
PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning
Alexander Krull, Eric Brachmann, Sebastian Nowozin +3
State-of-the-art computer vision algorithms often achieve efficiency by making discrete choices about which hypotheses to explore next. This allows allocation of computational reso…
DSAC - Differentiable RANSAC for Camera Localization
Eric Brachmann, Alexander Krull, Sebastian Nowozin +4
RANSAC is an important algorithm in robust optimization and a central building block for many computer vision applications. In recent years, traditionally hand-crafted pipelines ha…
DISCO Nets: DISsimilarity COefficient Networks
Diane Bouchacourt, M. Pawan Kumar, Sebastian Nowozin
We present a new type of probabilistic model which we call DISsimilarity COefficient Networks (DISCO Nets). DISCO Nets allow us to efficiently sample from a posterior distribution…
Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedo
Amit Adam, Christoph Dann, Omer Yair +2
We propose a computational model for shape, illumination and albedo inference in a pulsed time-of-flight (TOF) camera. In contrast to TOF cameras based on phase modulation, our cam…
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems
Jörg H. Kappes, Bjoern Andres, Fred A. Hamprecht +10
Szeliski et al. published an influential study in 2006 on energy minimization methods for Markov Random Fields (MRF). This study provided valuable insights in choosing the best opt…
Cascades of Regression Tree Fields for Image Restoration
Uwe Schmidt, Jeremy Jancsary, Sebastian Nowozin +2
Conditional random fields (CRFs) are popular discriminative models for computer vision and have been successfully applied in the domain of image restoration, especially to image de…
The Informed Sampler: A Discriminative Approach to Bayesian Inference in Generative Computer Vision Models
Varun Jampani, Sebastian Nowozin, Matthew Loper +1
Computer vision is hard because of a large variability in lighting, shape, and texture; in addition the image signal is non-additive due to occlusion. Generative models promised to…