99 citations · 122 across the 8 of their papers we have counts for
15 papers
Cascaded Multilingual Audio-Visual Learning from Videos
Andrew Rouditchenko, Angie Boggust, David Harwath +8
In this paper, we explore self-supervised audio-visual models that learn from instructional videos. Prior work has shown that these models can relate spoken words and sounds to vis…
Learning with Algorithmic Supervision via Continuous Relaxations
Felix Petersen, Christian Borgelt, Hilde Kuehne +1
The integration of algorithmic components into neural architectures has gained increased attention recently, as it allows training neural networks with new forms of supervision suc…
Style Agnostic 3D Reconstruction via Adversarial Style Transfer
Felix Petersen, Bastian Goldluecke, Oliver Deussen +1
Reconstructing the 3D geometry of an object from an image is a major challenge in computer vision. Recently introduced differentiable renderers can be leveraged to learn the 3D geo…
Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration without Forgetting
Anna Kukleva, Hilde Kuehne, Bernt Schiele
Both generalized and incremental few-shot learning have to deal with three major challenges: learning novel classes from only few samples per class, preventing catastrophic forgett…
Found a Reason for me? Weakly-supervised Grounded Visual Question Answering using Capsules
Aisha Urooj Khan, Hilde Kuehne, Kevin Duarte +3
The problem of grounding VQA tasks has seen an increased attention in the research community recently, with most attempts usually focusing on solving this task by using pretrained…
Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision
Felix Petersen, Christian Borgelt, Hilde Kuehne +1
Sorting and ranking supervision is a method for training neural networks end-to-end based on ordering constraints. That is, the ground truth order of sets of samples is known, whil…