Visual Inference

Visual Inference

The Visual Inference Lab at TU Darmstadt, led by Prof. Stefan Roth, conducts research in several areas of computer vision with an emphasis on statistical methods and machine learning. We develop mathematical models and algorithms for analyzing and processing digital images with the computer. For example, we work on semantic scene understanding, image motion estimation, deep learning, probabilistic methods, image restoration, and object tracking.

Moreover, we regularly offer courses, seminars and labs in computer science, particularly in computer vision and machine learning.

Recent Highlight

Darmstadt Noise Dataset: Ground truth data for image denoising with real image noise
Darmstadt Noise Dataset: Ground truth data for image denoising with real image noise

News & Events

  • CVPR 2019 Outstanding Reviewers

    June 9, 2019

    Jochen Gast, Junhwa Hur, and Anne Wannenwetsch were chosen as outstanding reviewers for CVPR 2019. Congratulations!

Recent Publications

  • CVPR 2019

    J. Hur and S. Roth, “Iterative residual refinement for joint optical flow and occlusion estimation.” [coming soon]

  • CVPR 2019

    N. Araslanov, C. Rothkopf, and S. Roth, “Actor-critic instance segmentation.” [coming soon]