28 citations · 30 across the 3 of their papers we have counts for
4 papers
Parting with Illusions about Deep Active Learning
Sudhanshu Mittal, Maxim Tatarchenko, Özgün Çiçek +1
Active learning aims to reduce the high labeling cost involved in training machine learning models on large datasets by efficiently labeling only the most informative samples. Rece…
Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Robotics
Oier Mees, Maxim Tatarchenko, Thomas Brox +1
We present a convolutional neural network for joint 3D shape prediction and viewpoint estimation from a single input image. During training, our network gets the learning signal fr…
Semi-Supervised Semantic Segmentation with High- and Low-level Consistency
Sudhanshu Mittal, Maxim Tatarchenko, Thomas Brox
The ability to understand visual information from limited labeled data is an important aspect of machine learning. While image-level classification has been extensively studied in…
What Do Single-view 3D Reconstruction Networks Learn?
Maxim Tatarchenko, Stephan R. Richter, René Ranftl +3
Convolutional networks for single-view object reconstruction have shown impressive performance and have become a popular subject of research. All existing techniques are united by…