6-DOF Model Based Tracking via Object Coordinate Regression. - Alexander Krull; Frank Michel 002; Eric Brachmann; Stefan Gumhold; Stephan Ihrke; Carsten Rother (ACCV (4), 2014)

Learning 6D Object Pose Estimation Using 3D Object Coordinates. - Eric Brachmann; Alexander Krull; Frank Michel 002; Stefan Gumhold; Jamie Shotton; Carsten Rother (ECCV (2), 2014)

Pose Estimation of Kinematic Chain Instances via Object Coordinate Regression. - Frank Michel 002; Alexander Krull; Eric Brachmann; Michael Ying Yang; Stefan Gumhold; Carsten Rother (BMVC, 2015)

Learning Analysis-by-Synthesis for 6D Pose Estimation in RGB-D Images. - Alexander Krull; Eric Brachmann; Frank Michel 002; Michael Ying Yang; Stefan Gumhold; Carsten Rother (ICCV, 2015)

Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image. - Eric Brachmann; Frank Michel 002; Alexander Krull; Michael Ying Yang; Stefan Gumhold; Carsten Rother (CVPR, 2016)

Random Forests versus Neural Networks - What's Best for Camera Relocalization? - Daniela Massiceti; Alexander Krull; Eric Brachmann; Carsten Rother; Philip H. S. Torr (CoRR, 2016)

DSAC - Differentiable RANSAC for Camera Localization. - Eric Brachmann; Alexander Krull; Sebastian Nowozin; Jamie Shotton; Frank Michel 002; Stefan Gumhold; Carsten Rother (CVPR, 2017)

PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning. - Alexander Krull; Eric Brachmann; Sebastian Nowozin; Frank Michel 002; Jamie Shotton; Carsten Rother (CVPR, 2017)

Global Hypothesis Generation for 6D Object Pose Estimation. - Frank Michel 002; Alexander Kirillov; Eric Brachmann; Alexander Krull; Stefan Gumhold; Bogdan Savchynskyy; Carsten Rother (CVPR, 2017)

Random forests versus Neural Networks - What's best for camera localization? - Daniela Massiceti; Alexander Krull; Eric Brachmann; Carsten Rother; Philip H. S. Torr (ICRA, 2017)

Learning Sampling-Based 6D Object Pose Estimation. - Alexander Krull (2017)

Noise2Void - Learning Denoising From Single Noisy Images. - Alexander Krull; Tim-Oliver Buchholz; Florian Jug (CVPR, 2019)

Probabilistic Noise2Void: Unsupervised Content-Aware Denoising. - Alexander Krull; Tomás Vicar; Florian Jug (CoRR, 2019)

DenoiSeg: Joint Denoising and Segmentation. - Tim-Oliver Buchholz; Mangal Prakash; Deborah Schmidt; Alexander Krull; Florian Jug (ECCV Workshops (1), 2020)

Improving Blind Spot Denoising for Microscopy. - Anna S. Goncharova; Alf Honigmann; Florian Jug; Alexander Krull (ECCV Workshops (1), 2020)

Removing Structured Noise with Self-Supervised Blind-Spot Networks. - Coleman Broaddus; Alexander Krull; Martin Weigert 001; Uwe Schmidt; Gene Myers (ISBI, 2020)

Leveraging Self-supervised Denoising for Image Segmentation. - Mangal Prakash; Tim-Oliver Buchholz; Manan Lalit; Pavel Tomancak; Florian Jug; Alexander Krull (ISBI, 2020)

Fully Unsupervised Probabilistic Noise2Void. - Mangal Prakash; Manan Lalit; Pavel Tomancak; Alexander Krull; Florian Jug (ISBI, 2020)

DenoiSeg: Joint Denoising and Segmentation. - Tim-Oliver Buchholz; Mangal Prakash; Alexander Krull; Florian Jug (CoRR, 2020)

DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders. - Mangal Prakash; Alexander Krull; Florian Jug (CoRR, 2020)

Probabilistic Noise2Void: Unsupervised Content-Aware Denoising. - Alexander Krull; Tomás Vicar; Mangal Prakash; Manan Lalit; Florian Jug (Frontiers Comput. Sci., 2020)

Fully Unsupervised Diversity Denoising with Convolutional Variational Autoencoders. - Mangal Prakash; Alexander Krull; Florian Jug (ICLR, 2021)

Towards Structured Noise Models for Unsupervised Denoising. - Benjamin Salmon; Alexander Krull (ECCV Workshops (4), 2022)

μSplit: efficient image decomposition for microscopy data. - Ashesh; Alexander Krull; Moises Di Sante; Francesco Silvio Pasqualini; Florian Jug (CoRR, 2022)

μSplit: image decomposition for fluorescence microscopy. - Ashesh; Alexander Krull; Moises Di Sante; Francesco Silvio Pasqualini; Florian Jug (ICCV, 2023)

Direct Unsupervised Denoising. - Benjamin Salmon; Alexander Krull (ICCV (Workshops), 2023)

Evaluating virtual staining for high-throughput screening. - Samuel Tonks; Chih-Yang Hsu; Steve Hood; Ryan Musso; Ceridwen Hopely; Steve Titus; Alexander Krull; Minh Doan; Iain B. Styles (ISBI, 2023)

Unsupervised Structured Noise Removal with Variational Lossy Autoencoder. - Benjamin Salmon; Alexander Krull (CoRR, 2023)

Can Virtual Staining for High-Throughput Screening Generalize? - Samuel Tonks; Cuong Q. Nguyen; Steve Hood; Ryan Musso; Ceridwen Hopely; Steve Titus; Minh Doan; Iain B. Styles; Alexander Krull (ECCV Workshops (16), 2024)

WiNet: Wavelet-Based Incremental Learning for Efficient Medical Image Registration. - Xinxing Cheng; Xi Jia; Wenqi Lu 001; Qiufu Li; Linlin Shen; Alexander Krull; Jinming Duan 001 (MICCAI (2), 2024)

bit2bit: 1-bit quanta video reconstruction via self-supervised photon prediction. - Yehe Liu; Alexander Krull; Hector Basevi; Ales Leonardis; Michael W. Jenkins (NeurIPS, 2024)

Image Denoising and the Generative Accumulation of Photons. - Alexander Krull; Hector Basevi; Benjamin Salmon; Andre Zeug; Franziska Müller 004; Samuel Tonks; Leela Muppala; Ales Leonardis (WACV, 2024)

Can virtual staining for high-throughput screening generalize? - Samuel Tonks; Cuong Nguyer; Steve Hood; Ryan Musso; Ceridwen Hopely; Steve Titus; Minh Doan; Iain B. Styles; Alexander Krull (CoRR, 2024)

Unsupervised Denoising for Signal-Dependent and Row-Correlated Imaging Noise. - Benjamin Salmon; Alexander Krull (WACV, 2025)

ShapeEmbed: a self-supervised learning framework for 2D contour quantification. - Anna Foix Romero; Craig Russell; Alexander Krull; Virginie Uhlmann (CoRR, 2025)