activity
20092023
most citedGuided Image Generation with Conditional Invertible Neural Networks

264 citations · 1.1k across the 53 of their papers we have counts for

collaborators

70 papers

cs.CV2023★ 2 cited

Unsupervised Deep Graph Matching Based on Cycle Consistency

Siddharth Tourani, Carsten Rother, Muhammad Haris Khan +1

We contribute to the sparsely populated area of unsupervised deep graph matching with application to keypoint matching in images. Contrary to the standard \emph{supervised} approac…

cs.LG2023

Finding Competence Regions in Domain Generalization

Jens Müller, Stefan T. Radev, Robert Schmier +3

We investigate a "learning to reject" framework to address the problem of silent failures in Domain Generalization (DG), where the test distribution differs from the training distr…

cs.CV2023★ 2 cited

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

Martin Sundermeyer, Tomas Hodan, Yann Labbe +5

We present the evaluation methodology, datasets and results of the BOP Challenge 2022, the fourth in a series of public competitions organized with the goal to capture the status q…

cs.CV2022★ 4 cited

A Comparative Study of Graph Matching Algorithms in Computer Vision

Stefan Haller, Lorenz Feineis, Lisa Hutschenreiter +5

The graph matching optimization problem is an essential component for many tasks in computer vision, such as bringing two deformable objects in correspondence. Naturally, a wide ra…

cs.CV2022

Towards Multimodal Depth Estimation from Light Fields

Titus Leistner, Radek Mackowiak, Lynton Ardizzone +2

Light field applications, especially light field rendering and depth estimation, developed rapidly in recent years. While state-of-the-art light field rendering methods handle semi…

cs.CV2022

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

Haebom Lee, Christian Homeyer, Robert Herzog +2

In this work, we focus on outdoor lighting estimation by aggregating individual noisy estimates from images, exploiting the rich image information from wide-angle cameras and/or te…