
Disentanglement by Nonlinear ICA with General Incompressibleflow Networks (GIN)
A central question of representation learning asks under which condition...
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SelfSupervised Viewpoint Learning From Image Collections
Training deep neural networks to estimate the viewpoint of objects requi...
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NeuralGuided RANSAC: Learning Where to Sample Model Hypotheses
We present NeuralGuided RANSAC (NGRANSAC), an extension to the classic...
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CONSAC: Robust MultiModel Fitting by Conditional Sample Consensus
We present a robust estimator for fitting multiple parametric models of ...
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Visual Camera ReLocalization from RGB and RGBD Images Using DSAC
We describe a learningbased system that estimates the camera position a...
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Analyzing Inverse Problems with Invertible Neural Networks
In many tasks, in particular in natural science, the goal is to determin...
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Reinforced Feature Points: Optimizing Feature Detection and Description for a HighLevel Task
We address a core problem of computer vision: Detection and description ...
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SplitMerge Pooling
There are a variety of approaches to obtain a vast receptive field with ...
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Learning to Think Outside the Box: WideBaseline Light Field Depth Estimation with EPIShift
We propose a method for depth estimation from light field data, based on...
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Guided Image Generation with Conditional Invertible Neural Networks
In this work, we address the task of natural image generation guided by ...
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A Summary of the 4th International Workshop on Recovering 6D Object Pose
This document summarizes the 4th International Workshop on Recovering 6D...
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Expert Sample Consensus Applied to Camera ReLocalization
Fitting model parameters to a set of noisy data points is a common probl...
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Intrinsic Autoencoders for Joint Neural Rendering and Intrinsic Image Decomposition
Neural rendering techniques promise efficient photorealistic image synt...
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Benchmarking the Robustness of Semantic Segmentation Models
When designing a semantic segmentation module for a practical applicatio...
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CEREALS  CostEffective REgionbased Active Learning for Semantic Segmentation
State of the art methods for semantic image segmentation are trained in ...
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Learning Less is More  6D Camera Localization via 3D Surface Regression
Popular research areas like autonomous driving and augmented reality hav...
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Augmented Reality Meets Computer Vision : Efficient Data Generation for Urban Driving Scenes
The success of deep learning in computer vision is based on availability...
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The Best of Both Worlds: Learning Geometrybased 6D Object Pose Estimation
We address the task of estimating the 6D pose of known rigid objects, fr...
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Analyzing Modular CNN Architectures for Joint Depth Prediction and Semantic Segmentation
This paper addresses the task of designing a modular neural network arch...
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Crowd Sourcing Image Segmentation with iaSTAPLE
We propose a novel label fusion technique as well as a crowdsourcing pro...
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Detecting Unexpected Obstacles for SelfDriving Cars: Fusing Deep Learning and Geometric Modeling
The detection of small road hazards, such as lost cargo, is a vital capa...
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A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching
We study the quadratic assignment problem, in computer vision also known...
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PoseAgent: BudgetConstrained 6D Object Pose Estimation via Reinforcement Learning
Stateoftheart computer vision algorithms often achieve efficiency by ...
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Global Hypothesis Generation for 6D Object Pose Estimation
This paper addresses the task of estimating the 6D pose of a known 3D ob...
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InstanceCut: from Edges to Instances with MultiCut
This work addresses the task of instanceaware semantic segmentation. Ou...
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DSAC  Differentiable RANSAC for Camera Localization
RANSAC is an important algorithm in robust optimization and a central bu...
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Joint Graph Decomposition and Node Labeling: Problem, Algorithms, Applications
We state a combinatorial optimization problem whose feasible solutions d...
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Can Ground Truth Label Propagation from Video help Semantic Segmentation?
For stateoftheart semantic segmentation task, training convolutional ...
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Random Forests versus Neural Networks  What's Best for Camera Localization?
This work addresses the task of camera localization in a known 3D scene ...
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Lost and Found: Detecting Small Road Hazards for SelfDriving Vehicles
Detecting small obstacles on the road ahead is a critical part of the dr...
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Stereo Video Deblurring
Videos acquired in lowlight conditions often exhibit motion blur, which...
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Joint MBestDiverse Labelings as a Parametric Submodular Minimization
We consider the problem of jointly inferring the Mbest diverse labeling...
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Convexity Shape Constraints for Image Segmentation
Segmenting an image into multiple components is a central task in comput...
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Relating Cascaded Random Forests to Deep Convolutional Neural Networks for Semantic Segmentation
We consider the task of pixelwise semantic segmentation given a small s...
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Curvature Prior for MRFbased Segmentation and Shape Inpainting
Most image labeling problems such as segmentation and image reconstructi...
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Learning an Interactive Segmentation System
Many successful applications of computer vision to image or video manipu...
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Panoptic Segmentation
We propose and study a novel 'Panoptic Segmentation' (PS) task. Panoptic...
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Deep Object CoSegmentation
This work presents a deep object cosegmentation (DOCS) approach for seg...
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Geometric Image Synthesis
The task of generating natural images from 3D scenes has been a long sta...
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BOP: Benchmark for 6D Object Pose Estimation
We propose a benchmark for 6D pose estimation of a rigid object from a s...
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Uncertaintyaware performance assessment of optical imaging modalities with invertible neural networks
Purpose: Optical imaging is evolving as a key technique for advanced sen...
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HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference
In this paper, we introduce Hierarchical Invertible Neural Transport (HI...
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Out of distribution detection for intraoperative functional imaging
Multispectral optical imaging is becoming a key tool in the operating ro...
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Exact Information Bottleneck with Invertible Neural Networks: Getting the Best of Discriminative and Generative Modeling
The Information Bottleneck (IB) principle offers a unified approach to m...
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A PrimalDual Solver for LargeScale TrackingbyAssignment
We propose a fast approximate solver for the combinatorial problem known...
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MPLP++: Fast, Parallel Dual BlockCoordinate Ascent for Dense Graphical Models
Dense, discrete Graphical Models with pairwise potentials are a powerful...
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Taxonomy of Dual BlockCoordinate Ascent Methods for Discrete Energy Minimization
We consider the maximumaposteriori inference problem in discrete graph...
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