9 citations · 9 across the 4 of their papers we have counts for
3 papers · 1 filter
Learning by Hallucinating: Vision-Language Pre-training with Weak Supervision
Tzu-Jui Julius Wang, Jorma Laaksonen, Tomas Langer +2
Weakly-supervised vision-language (V-L) pre-training (W-VLP) aims at learning cross-modal alignment with little or no paired data, such as aligned images and captions. Recent W-VLP…
No Shifted Augmentations (NSA): compact distributions for robust self-supervised Anomaly Detection
Mohamed Yousef, Marcel Ackermann, Unmesh Kurup +1
Unsupervised Anomaly detection (AD) requires building a notion of normalcy, distinguishing in-distribution (ID) and out-of-distribution (OOD) data, using only available ID samples.…
OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold
Mohamed Yousef, Tom E. Bishop
Text recognition is a major computer vision task with a big set of associated challenges. One of those traditional challenges is the coupled nature of text recognition and segmenta…