← Authors

Alexey Dosovitskiy

33 papers · 2013–2024 · 6 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (6) 🌈 Renaissance Researcher (6) 🐝 Cross-Pollinator (9) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (11) πŸ—ΊοΈ Taxonomy Completionist (55) 🧭 Keyword Pioneer πŸ”¬ Deep Specialist (10) 🧬 Topic Evolution 🀝 Dynamic Duo (14) πŸ—ƒοΈ Keyword Collector (113) ❓ The Questioner ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (33) πŸ”₯ Unstoppable (6)

Conferences

CVPR (10) NIPS (10) ICLR (5) CORL (4) ECCV (2) ICCV (2)

Top co-authors

Thomas Brox (14) Vladlen Koltun (7) Jakob Uszkoreit (5) Thomas Unterthiner (5) Eddy Ilg (4) Aravindh Mahendran (4) Dirk Weissenborn (4) Thomas Kipf (4) Georg Heigold (3) Daniel Cremers (3)

Keywords

convolutional neural network (10) representation learning (5) image generation (4) 3d reconstruction (4) image classification (3) vision transformer (3) optical flow estimation (3) optical flow (3) unsupervised learning (3) novel view synthesis (2) reinforcement learning (2) convolutional network (2) feature visualization (2) end-to-end learning (2) generative model (2) autonomous driving (2) video understanding (2) attention mechanism (2) scene representation (2) multi-layer perceptron (2)

Papers

ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization NIPS 2024
Moving Off-the-Grid: Scene-Grounded Video Representations NIPS 2024
Simple Open-Vocabulary Object Detection with Vision Transformers ECCV 2022
Conditional Object-Centric Learning from Video ICLR 2022
Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations CVPR 2022
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale ICLR 2021
NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections CVPR 2021
MLP-Mixer: An all-MLP Architecture for Vision NIPS 2021
Do Vision Transformers See Like Convolutional Neural Networks? NIPS 2021
Differentiable Patch Selection for Image Recognition CVPR 2021
You Only Train Once: Loss-Conditional Training of Deep Networks ICLR 2020
Object-Centric Learning with Slot Attention NIPS 2020
Deep Drone Racing: Learning Agile Flight in Dynamic Environments CORL 2018
Semi-parametric topological memory for navigation ICLR 2018
TD or not TD: Analyzing the Role of Temporal Differencing in Deep Reinforcement Learning ICLR 2018
Driving Policy Transfer via Modularity and Abstraction CORL 2018
On Offline Evaluation of Vision-based Driving Models ECCV 2018
Motion Perception in Reinforcement Learning with Dynamic Objects CORL 2018
Unsupervised Learning of Shape and Pose with Differentiable Point Clouds NIPS 2018
Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space CVPR 2017
DeMoN: Depth and Motion Network for Learning Monocular Stereo CVPR 2017
FlowNet 2.0: Evolution of Optical Flow Estimation With Deep Networks CVPR 2017
CARLA: An Open Urban Driving Simulator CORL 2017
Octree Generating Networks: Efficient Convolutional Architectures for High-Resolution 3D Outputs ICCV 2017
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation CVPR 2016
Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images NIPS 2016
Generating Images with Perceptual Similarity Metrics based on Deep Networks NIPS 2016
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks NIPS 2016
Inverting Visual Representations With Convolutional Networks CVPR 2016
FlowNet: Learning Optical Flow With Convolutional Networks ICCV 2015
Learning to Generate Chairs With Convolutional Neural Networks CVPR 2015
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks NIPS 2014
An Iterated L1 Algorithm for Non-smooth Non-convex Optimization in Computer Vision CVPR 2013