3D-reconstruction of indoor environments from human activity. - Barbara Frank; Michael Ruhnke; Maxim Tatarchenko; Wolfram Burgard (ICRA, 2015)

Single-view to Multi-view: Reconstructing Unseen Views with a Convolutional Network. - Maxim Tatarchenko; Alexey Dosovitskiy; Thomas Brox (CoRR, 2015)

Multi-view 3D Models from Single Images with a Convolutional Network. - Maxim Tatarchenko; Alexey Dosovitskiy; Thomas Brox (ECCV (7), 2016)

Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs. - Maxim Tatarchenko; Alexey Dosovitskiy; Thomas Brox (ICCV, 2017)

Learning to Generate Chairs, Tables and Cars with Convolutional Networks. - Alexey Dosovitskiy; Jost Tobias Springenberg; Maxim Tatarchenko; Thomas Brox (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

Tangent Convolutions for Dense Prediction in 3D. - Maxim Tatarchenko; Jaesik Park; Vladlen Koltun; Qian-Yi Zhou (CVPR, 2018)

What Do Single-View 3D Reconstruction Networks Learn? - Maxim Tatarchenko; Stephan R. Richter; René Ranftl; Zhuwen Li; Vladlen Koltun; Thomas Brox (CVPR, 2019)

Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Robotics. - Oier Mees; Maxim Tatarchenko; Thomas Brox; Wolfram Burgard (IROS, 2019)

ISOOV2 DL - Semantic Instance Segmentation of Touching and Overlapping Objects. - Anton Böhm; Maxim Tatarchenko; Thorsten Falk (ISBI, 2019)

Parting with Illusions about Deep Active Learning. - Sudhanshu Mittal; Maxim Tatarchenko; Özgün Çiçek; Thomas Brox (CoRR, 2019)

Scalable 3D deep learning: methods and applications. - Maxim Tatarchenko (2020)

Fostering Generalization in Single-View 3D Reconstruction by Learning a Hierarchy of Local and Global Shape Priors. - Jan Bechtold; Maxim Tatarchenko; Volker Fischer 003; Thomas Brox (CVPR, 2021)

Semi-Supervised Semantic Segmentation With High- and Low-Level Consistency. - Sudhanshu Mittal; Maxim Tatarchenko; Thomas Brox (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Histogram-based Deep Learning for Automotive Radar. - Maxim Tatarchenko; Kilian Rambach (CoRR, 2023)

Accurate Training Data for Occupancy Map Prediction in Automated Driving Using Evidence Theory. - Jonas Kälble; Sascha Wirges; Maxim Tatarchenko; Eddy Ilg (CVPR, 2024)

SceneTeller: Language-to-3D Scene Generation. - Basak Melis Öcal; Maxim Tatarchenko; Sezer Karaoglu; Theo Gevers (ECCV (85), 2024)

RealDiff: Real-world 3D Shape Completion using Self-Supervised Diffusion Models. - Basak Melis Öcal; Maxim Tatarchenko; Sezer Karaoglu; Theo Gevers (CoRR, 2024)

Image semantic segmentation of indoor scenes: A survey. - Ronny Velastegui; Maxim Tatarchenko; Sezer Karaoglu; Theo Gevers (Comput. Vis. Image Underst., 2024)

EvOcc: Accurate Semantic Occupancy for Automated Driving Using Evidence Theory. - Jonas Kälble; Sascha Wirges; Maxim Tatarchenko; Eddy Ilg (CVPR, 2025)

Realistic Evaluation of Deep Active Learning for Image Classification and Semantic Segmentation. - Sudhanshu Mittal; Joshua Niemeijer; Özgün Çiçek; Maxim Tatarchenko; Jan Ehrhardt; Jörg P. Schäfer; Heinz Handels; Thomas Brox (Int. J. Comput. Vis., 2025)