An Iterated L1 Algorithm for Non-smooth Non-convex Optimization in Computer Vision. - Peter Ochs; Alexey Dosovitskiy; Thomas Brox; Thomas Pock (CVPR, 2013)

Discriminative Unsupervised Feature Learning with Convolutional Neural Networks. - Alexey Dosovitskiy; Jost Tobias Springenberg; Martin A. Riedmiller; Thomas Brox (NIPS, 2014)

Unsupervised feature learning by augmenting single images. - Alexey Dosovitskiy; Jost Tobias Springenberg; Thomas Brox (ICLR (Workshop Poster), 2014)

Learning to generate chairs with convolutional neural networks. - Alexey Dosovitskiy; Jost Tobias Springenberg; Thomas Brox (CVPR, 2015)

Image Orientation Estimation with Convolutional Networks. - Philipp Fischer; Alexey Dosovitskiy; Thomas Brox (GCPR, 2015)

FlowNet: Learning Optical Flow with Convolutional Networks. - Alexey Dosovitskiy; Philipp Fischer; Eddy Ilg; Philip Häusser; Caner Hazirbas; Vladimir Golkov; Patrick van der Smagt; Daniel Cremers; Thomas Brox (ICCV, 2015)

q-Space Deep Learning for Twelve-Fold Shorter and Model-Free Diffusion MRI Scans. - Vladimir Golkov; Alexey Dosovitskiy; Philipp G. Sämann; Jonathan I. Sperl; Tim Sprenger; Michael Czisch; Marion I. Menzel; Pedro A. Gómez; Axel Haase; Thomas Brox; Daniel Cremers (MICCAI (1), 2015)

Inverting Convolutional Networks with Convolutional Networks. - Alexey Dosovitskiy; Thomas Brox (CoRR, 2015)

Striving for Simplicity: The All Convolutional Net. - Jost Tobias Springenberg; Alexey Dosovitskiy; Thomas Brox; Martin A. Riedmiller (ICLR (Workshop), 2015)

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

On Iteratively Reweighted Algorithms for Nonsmooth Nonconvex Optimization in Computer Vision. - Peter Ochs; Alexey Dosovitskiy; Thomas Brox; Thomas Pock (SIAM J. Imaging Sci., 2015)

Inverting Visual Representations with Convolutional Networks. - Alexey Dosovitskiy; Thomas Brox (CVPR, 2016)

A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation. - Nikolaus Mayer; Eddy Ilg; Philip Häusser; Philipp Fischer; Daniel Cremers; Alexey Dosovitskiy; Thomas Brox (CVPR, 2016)

Artistic Style Transfer for Videos. - Manuel Ruder; Alexey Dosovitskiy; Thomas Brox (GCPR, 2016)

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

Generating Images with Perceptual Similarity Metrics based on Deep Networks. - Alexey Dosovitskiy; Thomas Brox (NIPS, 2016)

Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images. - Vladimir Golkov; Marcin J. Skwark; Antonij Golkov; Alexey Dosovitskiy; Thomas Brox; Jens Meiler; Daniel Cremers (NIPS, 2016)

Synthesizing the preferred inputs for neurons in neural networks via deep generator networks. - Anh Mai Nguyen; Alexey Dosovitskiy; Jason Yosinski; Thomas Brox; Jeff Clune (NIPS, 2016)

Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks. - Alexey Dosovitskiy; Philipp Fischer; Jost Tobias Springenberg; Martin A. Riedmiller; Thomas Brox (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI Scans. - Vladimir Golkov; Alexey Dosovitskiy; Jonathan I. Sperl; Marion I. Menzel; Michael Czisch; Philipp G. Sämann; Thomas Brox; Daniel Cremers (IEEE Trans. Medical Imaging, 2016)

CARLA: An Open Urban Driving Simulator. - Alexey Dosovitskiy; Germán Ros; Felipe Codevilla; Antonio M. López 001; Vladlen Koltun (CoRL, 2017)

FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks. - Eddy Ilg; Nikolaus Mayer; Tonmoy Saikia; Margret Keuper; Alexey Dosovitskiy; Thomas Brox (CVPR, 2017)

Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space. - Anh Nguyen 002; Jeff Clune; Yoshua Bengio; Alexey Dosovitskiy; Jason Yosinski (CVPR, 2017)

DeMoN: Depth and Motion Network for Learning Monocular Stereo. - Benjamin Ummenhofer; Huizhong Zhou; Jonas Uhrig; Nikolaus Mayer; Eddy Ilg; Alexey Dosovitskiy; Thomas Brox (CVPR, 2017)

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

Learning to Act by Predicting the Future. - Alexey Dosovitskiy; Vladlen Koltun (ICLR, 2017)

MINOS: Multimodal Indoor Simulator for Navigation in Complex Environments. - Manolis Savva; Angel X. Chang; Alexey Dosovitskiy; Thomas A. Funkhouser; Vladlen Koltun (CoRR, 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)

Motion Perception in Reinforcement Learning with Dynamic Objects. - Artemij Amiranashvili; Alexey Dosovitskiy; Vladlen Koltun; Thomas Brox (CoRL, 2018)

Deep Drone Racing: Learning Agile Flight in Dynamic Environments. - Elia Kaufmann; Antonio Loquercio; René Ranftl; Alexey Dosovitskiy; Vladlen Koltun; Davide Scaramuzza 001 (CoRL, 2018)

Driving Policy Transfer via Modularity and Abstraction. - Matthias Müller 011; Alexey Dosovitskiy; Bernard Ghanem; Vladlen Koltun (CoRL, 2018)

On Offline Evaluation of Vision-Based Driving Models. - Felipe Codevilla; Antonio M. López 001; Vladlen Koltun; Alexey Dosovitskiy (ECCV (15), 2018)

TD or not TD: Analyzing the Role of Temporal Differencing in Deep Reinforcement Learning. - Artemij Amiranashvili; Alexey Dosovitskiy; Vladlen Koltun; Thomas Brox (ICLR (Poster), 2018)

Semi-parametric topological memory for navigation. - Nikolay Savinov; Alexey Dosovitskiy; Vladlen Koltun (ICLR (Poster), 2018)

End-to-End Driving Via Conditional Imitation Learning. - Felipe Codevilla; Matthias Müller 011; Antonio M. López 001; Vladlen Koltun; Alexey Dosovitskiy (ICRA, 2018)

Unsupervised Learning of Shape and Pose with Differentiable Point Clouds. - Eldar Insafutdinov; Alexey Dosovitskiy (NeurIPS, 2018)

On Evaluation of Embodied Navigation Agents. - Peter Anderson 001; Angel X. Chang; Devendra Singh Chaplot; Alexey Dosovitskiy; Saurabh Gupta 001; Vladlen Koltun; Jana Kosecka; Jitendra Malik; Roozbeh Mottaghi; Manolis Savva; Amir R. Zamir (CoRR, 2018)

What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? - Nikolaus Mayer; Eddy Ilg; Philipp Fischer; Caner Hazirbas; Daniel Cremers; Alexey Dosovitskiy; Thomas Brox (Int. J. Comput. Vis., 2018)

Artistic Style Transfer for Videos and Spherical Images. - Manuel Ruder; Alexey Dosovitskiy; Thomas Brox (Int. J. Comput. Vis., 2018)

Learning to Predict the Wind for Safe Aerial Vehicle Planning. - Florian Achermann; Nicholas R. J. Lawrance; René Ranftl; Alexey Dosovitskiy; Jen Jen Chung; Roland Siegwart (ICRA, 2019)

Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing. - Elia Kaufmann; Mathias Gehrig; Philipp Foehn; René Ranftl; Alexey Dosovitskiy; Vladlen Koltun; Davide Scaramuzza 001 (ICRA, 2019)

Learning agile and dynamic motor skills for legged robots. - Jemin Hwangbo; Joonho Lee; Alexey Dosovitskiy; Dario Bellicoso; Vassilios Tsounis; Vladlen Koltun; Marco Hutter 001 (CoRR, 2019)

Benchmarking Classic and Learned Navigation in Complex 3D Environments. - Dmytro Mishkin; Alexey Dosovitskiy; Vladlen Koltun (CoRR, 2019)

The Visual Task Adaptation Benchmark. - Xiaohua Zhai; Joan Puigcerver; Alexander Kolesnikov 003; Pierre Ruyssen; Carlos Riquelme; Mario Lucic; Josip Djolonga; André Susano Pinto; Maxim Neumann; Alexey Dosovitskiy; Lucas Beyer; Olivier Bachem; et al. (CoRR, 2019)

Frequency-Aware Model Predictive Control. - Ruben Grandia; Farbod Farshidian; Alexey Dosovitskiy; René Ranftl; Marco Hutter 001 (IEEE Robotics Autom. Lett., 2019)

Where Should I Walk? Predicting Terrain Properties From Images Via Self-Supervised Learning. - Lorenz Wellhausen; Alexey Dosovitskiy; René Ranftl; Krzysztof Walas; Cesar Cadena 001; Marco Hutter 001 (IEEE Robotics Autom. Lett., 2019)

Learning agile and dynamic motor skills for legged robots. - Joonho Lee; Alexey Dosovitskiy; Dario Bellicoso; Vassilios Tsounis; Vladlen Koltun; Marco Hutter 001 (Sci. Robotics, 2019)

You Only Train Once: Loss-Conditional Training of Deep Networks. - Alexey Dosovitskiy; Josip Djolonga (ICLR, 2020)

Object-Centric Learning with Slot Attention. - Francesco Locatello; Dirk Weissenborn; Thomas Unterthiner; Aravindh Mahendran; Georg Heigold; Jakob Uszkoreit; Alexey Dosovitskiy; Thomas Kipf (NeurIPS, 2020)

Learning Depth via Interaction. - Antonio Loquercio; Alexey Dosovitskiy; Davide Scaramuzza 001 (CoRR, 2020)

Learning Object-Centric Video Models by Contrasting Sets. - Sindy Löwe; Klaus Greff; Rico Jonschkowski; Alexey Dosovitskiy; Thomas Kipf (CoRR, 2020)

Learning Depth With Very Sparse Supervision. - Antonio Loquercio; Alexey Dosovitskiy; Davide Scaramuzza 001 (IEEE Robotics Autom. Lett., 2020)

Deep Drone Racing: From Simulation to Reality With Domain Randomization. - Antonio Loquercio; Elia Kaufmann; René Ranftl; Alexey Dosovitskiy; Vladlen Koltun; Davide Scaramuzza 001 (IEEE Trans. Robotics, 2020)

Differentiable Patch Selection for Image Recognition. - Jean-Baptiste Cordonnier; Aravindh Mahendran; Alexey Dosovitskiy; Dirk Weissenborn; Jakob Uszkoreit; Thomas Unterthiner (CVPR, 2021)

NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections. - Ricardo Martin-Brualla; Noha Radwan; Mehdi S. M. Sajjadi; Jonathan T. Barron; Alexey Dosovitskiy; Daniel Duckworth (CVPR, 2021)

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. - Alexey Dosovitskiy; Lucas Beyer; Alexander Kolesnikov 003; Dirk Weissenborn; Xiaohua Zhai; Thomas Unterthiner; Mostafa Dehghani 001; Matthias Minderer; Georg Heigold; Sylvain Gelly; Jakob Uszkoreit; Neil Houlsby (ICLR, 2021)

Do Vision Transformers See Like Convolutional Neural Networks? - Maithra Raghu; Thomas Unterthiner; Simon Kornblith; Chiyuan Zhang; Alexey Dosovitskiy (NeurIPS, 2021)

MLP-Mixer: An all-MLP Architecture for Vision. - Ilya O. Tolstikhin; Neil Houlsby; Alexander Kolesnikov 003; Lucas Beyer; Xiaohua Zhai; Thomas Unterthiner; Jessica Yung; Andreas Steiner 001; Daniel Keysers; Jakob Uszkoreit; Mario Lucic; Alexey Dosovitskiy (NeurIPS, 2021)

Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations. - Mehdi S. M. Sajjadi; Henning Meyer; Etienne Pot; Urs Bergmann; Klaus Greff; Noha Radwan; Suhani Vora; Mario Lucic; Daniel Duckworth; Alexey Dosovitskiy; Jakob Uszkoreit; Thomas A. Funkhouser; et al. (CVPR, 2022)

Simple Open-Vocabulary Object Detection. - Matthias Minderer; Alexey A. Gritsenko; Austin Stone; Maxim Neumann; Dirk Weissenborn; Alexey Dosovitskiy; Aravindh Mahendran; Anurag Arnab; Mostafa Dehghani 001; Zhuoran Shen; Xiao Wang 038; Xiaohua Zhai; et al. (ECCV (10), 2022)

Conditional Object-Centric Learning from Video. - Thomas Kipf; Gamaleldin Fathy Elsayed; Aravindh Mahendran; Austin Stone; Sara Sabour; Georg Heigold; Rico Jonschkowski; Alexey Dosovitskiy; Klaus Greff (ICLR, 2022)

Simple Open-Vocabulary Object Detection with Vision Transformers. - Matthias Minderer; Alexey A. Gritsenko; Austin Stone; Maxim Neumann; Dirk Weissenborn; Alexey Dosovitskiy; Aravindh Mahendran; Anurag Arnab; Mostafa Dehghani 001; Zhuoran Shen; Xiao Wang 038; Xiaohua Zhai; et al. (CoRR, 2022)

ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization. - Luca Eyring; Shyamgopal Karthik; Karsten Roth; Alexey Dosovitskiy; Zeynep Akata (NeurIPS, 2024)

Moving Off-the-Grid: Scene-Grounded Video Representations. - Sjoerd van Steenkiste; Daniel Zoran; Yi Yang 007; Yulia Rubanova; Rishabh Kabra; Carl Doersch; Dilara Gokay; Joseph Heyward; Etienne Pot; Klaus Greff; Drew A. Hudson; Thomas Keck; et al. (NeurIPS, 2024)

Noise Hypernetworks: Amortizing Test-Time Compute in Diffusion Models. - Luca Eyring; Shyamgopal Karthik; Alexey Dosovitskiy; Nataniel Ruiz; Zeynep Akata (CoRR, 2025)