Carsten Rother

research

∙ 03/17/2023

Finding Competence Regions in Domain Generalization

We propose a "learning to reject" framework to address the problem of si...

0 Jens Müller, et al. ∙

research

∙ 02/25/2023

BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects

We present the evaluation methodology, datasets and results of the BOP C...

2 Martin Sundermeyer, et al. ∙

research

∙ 07/01/2022

A Comparative Study of Graph Matching Algorithms in Computer Vision

The graph matching optimization problem is an essential component for ma...

8 Stefan Haller, et al. ∙

research

∙ 03/30/2022

Towards Multimodal Depth Estimation from Light Fields

Light field applications, especially light field rendering and depth est...

0 Titus Leistner, et al. ∙

research

∙ 02/18/2022

Spatio-Temporal Outdoor Lighting Aggregation on Image Sequences using Transformer Networks

In this work, we focus on outdoor lighting estimation by aggregating ind...

2 Haebom Lee, et al. ∙

research

∙ 01/31/2022

Exoplanet Characterization using Conditional Invertible Neural Networks

The characterization of an exoplanet's interior is an inverse problem, w...

0 Jonas Haldemann, et al. ∙

research

∙ 12/02/2021

Neural Head Avatars from Monocular RGB Videos

We present Neural Head Avatars, a novel neural representation that expli...

0 Philip-William Grassal, et al. ∙

research

∙ 10/19/2021

Self-Supervised Object Detection via Generative Image Synthesis

We present SSOD, the first end-to-end analysis-by synthesis framework wi...

20 Siva Karthik Mustikovela, et al. ∙

research

∙ 09/01/2021

On the Limits of Pseudo Ground Truth in Visual Camera Re-localisation

Benchmark datasets that measure camera pose accuracy have driven progres...

23 Eric Brachmann, et al. ∙

research

∙ 05/05/2021

Conditional Invertible Neural Networks for Diverse Image-to-Image Translation

We introduce a new architecture called a conditional invertible neural n...

6 Lynton Ardizzone, et al. ∙

research

∙ 01/28/2021

Fusion Moves for Graph Matching

We contribute to approximate algorithms for the quadratic assignment pro...

0 Lisa Hutschenreiter, et al. ∙

research

∙ 01/26/2021

Benchmarking Invertible Architectures on Inverse Problems

Recent work demonstrated that flow-based invertible neural networks are ...

0 Jakob Kruse, et al. ∙

research

∙ 12/15/2020

Representing Ambiguity in Registration Problems with Conditional Invertible Neural Networks

Image registration is the basis for many applications in the fields of m...

9 Darya Trofimova, et al. ∙

research

∙ 11/10/2020

Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging

Multispectral photoacoustic imaging (PAI) is an emerging imaging modalit...

3 Jan-Hinrich Nölke, et al. ∙

research

∙ 10/14/2020

Learning Robust Models Using The Principle of Independent Causal Mechanisms

Standard supervised learning breaks down under data distribution shift. ...

0 Jens Müller, et al. ∙

research

∙ 10/12/2020

Increasing the Robustness of Semantic Segmentation Models with Painting-by-Numbers

For safety-critical applications such as autonomous driving, CNNs have t...

8 Christoph Kamann, et al. ∙

research

∙ 09/15/2020

BOP Challenge 2020 on 6D Object Localization

This paper presents the evaluation methodology, datasets, and results of...

27 Tomas Hodan, et al. ∙

research

∙ 07/29/2020

Generative Classifiers as a Basis for Trustworthy Computer Vision

With the maturing of deep learning systems, trustworthiness is becoming ...

9 Radek Mackowiak, et al. ∙

research

∙ 06/29/2020

Intrinsic Autoencoders for Joint Neural Rendering and Intrinsic Image Decomposition

Neural rendering techniques promise efficient photo-realistic image synt...

10 Hassan Abu Alhaija, et al. ∙

research

∙ 06/13/2020

Split-Merge Pooling

There are a variety of approaches to obtain a vast receptive field with ...

17 Omid Hosseini Jafari, et al. ∙

research

∙ 04/16/2020

MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models

Dense, discrete Graphical Models with pairwise potentials are a powerful...

0 Siddharth Tourani, et al. ∙

research

∙ 04/16/2020

Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization

We consider the maximum-a-posteriori inference problem in discrete graph...

0 Siddharth Tourani, et al. ∙

research

∙ 04/14/2020

A Primal-Dual Solver for Large-Scale Tracking-by-Assignment

We propose a fast approximate solver for the combinatorial problem known...

0 Stefan Haller, et al. ∙

research

∙ 04/03/2020

Self-Supervised Viewpoint Learning From Image Collections

Training deep neural networks to estimate the viewpoint of objects requi...

36 Siva Karthik Mustikovela, et al. ∙

research

∙ 02/27/2020

Visual Camera Re-Localization from RGB and RGB-D Images Using DSAC

We describe a learning-based system that estimates the camera position a...

21 Eric Brachmann, et al. ∙

research

∙ 01/17/2020

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...

0 Lynton Ardizzone, et al. ∙

research

∙ 01/14/2020

Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)

A central question of representation learning asks under which condition...

65 Peter Sorrenson, et al. ∙

research

∙ 01/08/2020

CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus

We present a robust estimator for fitting multiple parametric models of ...

26 Florian Kluger, et al. ∙

research

∙ 12/02/2019

Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task

We address a core problem of computer vision: Detection and description ...

19 Aritra Bhowmik, et al. ∙

research

∙ 11/05/2019

Out of distribution detection for intra-operative functional imaging

Multispectral optical imaging is becoming a key tool in the operating ro...

0 Tim J. Adler, et al. ∙

research

∙ 09/19/2019

Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift

We propose a method for depth estimation from light field data, based on...

16 Titus Leistner, et al. ∙

research

∙ 08/14/2019

Benchmarking the Robustness of Semantic Segmentation Models

When designing a semantic segmentation module for a practical applicatio...

8 Christoph Kamann, et al. ∙

research

∙ 08/07/2019

Expert Sample Consensus Applied to Camera Re-Localization

Fitting model parameters to a set of noisy data points is a common probl...

11 Eric Brachmann, et al. ∙

research

∙ 07/04/2019

Guided Image Generation with Conditional Invertible Neural Networks

In this work, we address the task of natural image generation guided by ...

13 Lynton Ardizzone, et al. ∙

research

∙ 05/25/2019

HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference

In this paper, we introduce Hierarchical Invertible Neural Transport (HI...

0 Gianluca Detommaso, et al. ∙

research

∙ 05/10/2019

Neural-Guided RANSAC: Learning Where to Sample Model Hypotheses

We present Neural-Guided RANSAC (NG-RANSAC), an extension to the classic...

26 Eric Brachmann, et al. ∙

research

∙ 03/08/2019

Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks

Purpose: Optical imaging is evolving as a key technique for advanced sen...

0 Tim J. Adler, et al. ∙

research

∙ 10/23/2018

CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation

State of the art methods for semantic image segmentation are trained in ...

4 Radek Mackowiak, et al. ∙

research

∙ 10/09/2018

A Summary of the 4th International Workshop on Recovering 6D Object Pose

This document summarizes the 4th International Workshop on Recovering 6D...

12 Tomas Hodan, et al. ∙

research

∙ 09/12/2018

Geometric Image Synthesis

The task of generating natural images from 3D scenes has been a long sta...

0 Hassan Abu Alhaija, et al. ∙

research

∙ 08/24/2018

BOP: Benchmark for 6D Object Pose Estimation

We propose a benchmark for 6D pose estimation of a rigid object from a s...

0 Tomas Hodan, et al. ∙

research

∙ 08/14/2018

Analyzing Inverse Problems with Invertible Neural Networks

In many tasks, in particular in natural science, the goal is to determin...

20 Lynton Ardizzone, et al. ∙

research

∙ 04/17/2018

Deep Object Co-Segmentation

This work presents a deep object co-segmentation (DOCS) approach for seg...

0 Weihao Li, et al. ∙

research

∙ 01/03/2018

Panoptic Segmentation

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

0 Alexander Kirillov, et al. ∙

research

∙ 12/05/2017

The Best of Both Worlds: Learning Geometry-based 6D Object Pose Estimation

We address the task of estimating the 6D pose of known rigid objects, fr...

0 Omid Hosseini Jafari, et al. ∙

research

∙ 11/28/2017

Learning Less is More - 6D Camera Localization via 3D Surface Regression

Popular research areas like autonomous driving and augmented reality hav...

0 Eric Brachmann, et al. ∙

research

∙ 08/04/2017

Augmented Reality Meets Computer Vision : Efficient Data Generation for Urban Driving Scenes

The success of deep learning in computer vision is based on availability...

0 Hassan Abu Alhaija, et al. ∙

research

∙ 02/26/2017

Analyzing Modular CNN Architectures for Joint Depth Prediction and Semantic Segmentation

This paper addresses the task of designing a modular neural network arch...

0 Omid Hosseini Jafari, et al. ∙

research

∙ 02/21/2017

Crowd Sourcing Image Segmentation with iaSTAPLE

We propose a novel label fusion technique as well as a crowdsourcing pro...

0 Dmitrij Schlesinger, et al. ∙

research

∙ 12/20/2016

Detecting Unexpected Obstacles for Self-Driving Cars: Fusing Deep Learning and Geometric Modeling

The detection of small road hazards, such as lost cargo, is a vital capa...

0 Sebastian Ramos, et al. ∙

Carsten Rother

Featured Co-authors