604 citations · 1k across the 14 of their papers we have counts for
4 papers · 1 filter
Scale-Equivariant Deep Learning for 3D Data
Thomas Wimmer, Vladimir Golkov, Hoai Nam Dang +3
The ability of convolutional neural networks (CNNs) to recognize objects regardless of their position in the image is due to the translation-equivariance of the convolutional opera…
Scene Graph Generation for Better Image Captioning?
Maximilian Mozes, Martin Schmitt, Vladimir Golkov +2
We investigate the incorporation of visual relationships into the task of supervised image caption generation by proposing a model that leverages detected objects and auto-generate…
Rotation-Equivariant Deep Learning for Diffusion MRI
Philip Müller, Vladimir Golkov, Valentina Tomassini +1
Convolutional networks are successful, but they have recently been outperformed by new neural networks that are equivariant under rotations and translations. These new networks wor…
FlowNet: Learning Optical Flow with Convolutional Networks
Philipp Fischer, Alexey Dosovitskiy, Eddy Ilg +6
Convolutional neural networks (CNNs) have recently been very successful in a variety of computer vision tasks, especially on those linked to recognition. Optical flow estimation ha…