32 citations · 43 across the 5 of their papers we have counts for
10 papers · 1 filter
MorphGAN: One-Shot Face Synthesis GAN for Detecting Recognition Bias
Nataniel Ruiz, Barry-John Theobald, Anurag Ranjan +2
To detect bias in face recognition networks, it can be useful to probe a network under test using samples in which only specific attributes vary in some controlled way. However, ca…
Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding
Mike Roberts, Jason Ramapuram, Anurag Ranjan +5
For many fundamental scene understanding tasks, it is difficult or impossible to obtain per-pixel ground truth labels from real images. We address this challenge by introducing Hyp…
GIF: Generative Interpretable Faces
Partha Ghosh, Pravir Singh Gupta, Roy Uziel +3
Photo-realistic visualization and animation of expressive human faces have been a long standing challenge. 3D face modeling methods provide parametric control but generates unreali…
Attacking Optical Flow
Anurag Ranjan, Joel Janai, Andreas Geiger +1
Deep neural nets achieve state-of-the-art performance on the problem of optical flow estimation. Since optical flow is used in several safety-critical applications like self-drivin…
Learning Multi-Human Optical Flow
Anurag Ranjan, David T. Hoffmann, Dimitrios Tzionas +3
The optical flow of humans is well known to be useful for the analysis of human action. Recent optical flow methods focus on training deep networks to approach the problem. However…
Learning to Dress 3D People in Generative Clothing
Qianli Ma, Jinlong Yang, Anurag Ranjan +4
Three-dimensional human body models are widely used in the analysis of human pose and motion. Existing models, however, are learned from minimally-clothed 3D scans and thus do not…