
Fusion Moves for Graph Matching
We contribute to approximate algorithms for the quadratic assignment pro...
read it

Benchmarking Invertible Architectures on Inverse Problems
Recent work demonstrated that flowbased invertible neural networks are ...
read it

Representing Ambiguity in Registration Problems with Conditional Invertible Neural Networks
Image registration is the basis for many applications in the fields of m...
read it

Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging
Multispectral photoacoustic imaging (PAI) is an emerging imaging modalit...
read it

Learning Robust Models Using The Principle of Independent Causal Mechanisms
Standard supervised learning breaks down under data distribution shift. ...
read it

Increasing the Robustness of Semantic Segmentation Models with PaintingbyNumbers
For safetycritical applications such as autonomous driving, CNNs have t...
read it

BOP Challenge 2020 on 6D Object Localization
This paper presents the evaluation methodology, datasets, and results of...
read it

Generative Classifiers as a Basis for Trustworthy Computer Vision
With the maturing of deep learning systems, trustworthiness is becoming ...
read it

Intrinsic Autoencoders for Joint Neural Rendering and Intrinsic Image Decomposition
Neural rendering techniques promise efficient photorealistic image synt...
read it

SplitMerge Pooling
There are a variety of approaches to obtain a vast receptive field with ...
read it

MPLP++: Fast, Parallel Dual BlockCoordinate Ascent for Dense Graphical Models
Dense, discrete Graphical Models with pairwise potentials are a powerful...
read it

Taxonomy of Dual BlockCoordinate Ascent Methods for Discrete Energy Minimization
We consider the maximumaposteriori inference problem in discrete graph...
read it

A PrimalDual Solver for LargeScale TrackingbyAssignment
We propose a fast approximate solver for the combinatorial problem known...
read it

SelfSupervised Viewpoint Learning From Image Collections
Training deep neural networks to estimate the viewpoint of objects requi...
read it

Visual Camera ReLocalization from RGB and RGBD Images Using DSAC
We describe a learningbased system that estimates the camera position a...
read it

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...
read it

Disentanglement by Nonlinear ICA with General Incompressibleflow Networks (GIN)
A central question of representation learning asks under which condition...
read it

CONSAC: Robust MultiModel Fitting by Conditional Sample Consensus
We present a robust estimator for fitting multiple parametric models of ...
read it

Reinforced Feature Points: Optimizing Feature Detection and Description for a HighLevel Task
We address a core problem of computer vision: Detection and description ...
read it

Out of distribution detection for intraoperative functional imaging
Multispectral optical imaging is becoming a key tool in the operating ro...
read it

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...
read it

Benchmarking the Robustness of Semantic Segmentation Models
When designing a semantic segmentation module for a practical applicatio...
read it

Expert Sample Consensus Applied to Camera ReLocalization
Fitting model parameters to a set of noisy data points is a common probl...
read it

Guided Image Generation with Conditional Invertible Neural Networks
In this work, we address the task of natural image generation guided by ...
read it

HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference
In this paper, we introduce Hierarchical Invertible Neural Transport (HI...
read it

NeuralGuided RANSAC: Learning Where to Sample Model Hypotheses
We present NeuralGuided RANSAC (NGRANSAC), an extension to the classic...
read it

Uncertaintyaware performance assessment of optical imaging modalities with invertible neural networks
Purpose: Optical imaging is evolving as a key technique for advanced sen...
read it

CEREALS  CostEffective REgionbased Active Learning for Semantic Segmentation
State of the art methods for semantic image segmentation are trained in ...
read it

A Summary of the 4th International Workshop on Recovering 6D Object Pose
This document summarizes the 4th International Workshop on Recovering 6D...
read it

Geometric Image Synthesis
The task of generating natural images from 3D scenes has been a long sta...
read it

BOP: Benchmark for 6D Object Pose Estimation
We propose a benchmark for 6D pose estimation of a rigid object from a s...
read it

Analyzing Inverse Problems with Invertible Neural Networks
In many tasks, in particular in natural science, the goal is to determin...
read it

Deep Object CoSegmentation
This work presents a deep object cosegmentation (DOCS) approach for seg...
read it

Panoptic Segmentation
We propose and study a novel 'Panoptic Segmentation' (PS) task. Panoptic...
read it

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...
read it

Learning Less is More  6D Camera Localization via 3D Surface Regression
Popular research areas like autonomous driving and augmented reality hav...
read it

Augmented Reality Meets Computer Vision : Efficient Data Generation for Urban Driving Scenes
The success of deep learning in computer vision is based on availability...
read it

Analyzing Modular CNN Architectures for Joint Depth Prediction and Semantic Segmentation
This paper addresses the task of designing a modular neural network arch...
read it

Crowd Sourcing Image Segmentation with iaSTAPLE
We propose a novel label fusion technique as well as a crowdsourcing pro...
read it

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...
read it

A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching
We study the quadratic assignment problem, in computer vision also known...
read it

PoseAgent: BudgetConstrained 6D Object Pose Estimation via Reinforcement Learning
Stateoftheart computer vision algorithms often achieve efficiency by ...
read it

Global Hypothesis Generation for 6D Object Pose Estimation
This paper addresses the task of estimating the 6D pose of a known 3D ob...
read it

InstanceCut: from Edges to Instances with MultiCut
This work addresses the task of instanceaware semantic segmentation. Ou...
read it

DSAC  Differentiable RANSAC for Camera Localization
RANSAC is an important algorithm in robust optimization and a central bu...
read it

Joint Graph Decomposition and Node Labeling: Problem, Algorithms, Applications
We state a combinatorial optimization problem whose feasible solutions d...
read it

Can Ground Truth Label Propagation from Video help Semantic Segmentation?
For stateoftheart semantic segmentation task, training convolutional ...
read it

Random Forests versus Neural Networks  What's Best for Camera Localization?
This work addresses the task of camera localization in a known 3D scene ...
read it

Lost and Found: Detecting Small Road Hazards for SelfDriving Vehicles
Detecting small obstacles on the road ahead is a critical part of the dr...
read it

Stereo Video Deblurring
Videos acquired in lowlight conditions often exhibit motion blur, which...
read it