6 citations · 12 across the 6 of their papers we have counts for
9 papers
Unified Fully and Timestamp Supervised Temporal Action Segmentation via Sequence to Sequence Translation
Nadine Behrmann, S. Alireza Golestaneh, Zico Kolter +2
This paper introduces a unified framework for video action segmentation via sequence to sequence (seq2seq) translation in a fully and timestamp supervised setup. In contrast to cur…
Ranking Info Noise Contrastive Estimation: Boosting Contrastive Learning via Ranked Positives
David T. Hoffmann, Nadine Behrmann, Juergen Gall +2
This paper introduces Ranking Info Noise Contrastive Estimation (RINCE), a new member in the family of InfoNCE losses that preserves a ranked ordering of positive samples. In contr…
Long Short View Feature Decomposition via Contrastive Video Representation Learning
Nadine Behrmann, Mohsen Fayyaz, Juergen Gall +1
Self-supervised video representation methods typically focus on the representation of temporal attributes in videos. However, the role of stationary versus non-stationary attribute…
Self-labeled Conditional GANs
Mehdi Noroozi
This paper introduces a novel and fully unsupervised framework for conditional GAN training in which labels are automatically obtained from data. We incorporate a clustering networ…
Unsupervised Video Representation Learning by Bidirectional Feature Prediction
Nadine Behrmann, Juergen Gall, Mehdi Noroozi
This paper introduces a novel method for self-supervised video representation learning via feature prediction. In contrast to the previous methods that focus on future feature pred…
3D CNNs with Adaptive Temporal Feature Resolutions
Mohsen Fayyaz, Emad Bahrami, Ali Diba +4
While state-of-the-art 3D Convolutional Neural Networks (CNN) achieve very good results on action recognition datasets, they are computationally very expensive and require many GFL…