7 citations · 21 across the 7 of their papers we have counts for
8 papers · 1 filter
Meta Internal Learning
Raphael Bensadoun, Shir Gur, Tomer Galanti +1
Internal learning for single-image generation is a framework, where a generator is trained to produce novel images based on a single image. Since these models are trained on a sing…
Cross-Modal Retrieval Augmentation for Multi-Modal Classification
Shir Gur, Natalia Neverova, Chris Stauffer +3
Recent advances in using retrieval components over external knowledge sources have shown impressive results for a variety of downstream tasks in natural language processing. Here,…
Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers
Hila Chefer, Shir Gur, Lior Wolf
Transformers are increasingly dominating multi-modal reasoning tasks, such as visual question answering, achieving state-of-the-art results thanks to their ability to contextualize…
Visualization of Supervised and Self-Supervised Neural Networks via Attribution Guided Factorization
Shir Gur, Ameen Ali, Lior Wolf
Neural network visualization techniques mark image locations by their relevancy to the network's classification. Existing methods are effective in highlighting the regions that aff…
Transformer Interpretability Beyond Attention Visualization
Hila Chefer, Shir Gur, Lior Wolf
Self-attention techniques, and specifically Transformers, are dominating the field of text processing and are becoming increasingly popular in computer vision classification tasks.…
Hierarchical Patch VAE-GAN: Generating Diverse Videos from a Single Sample
Shir Gur, Sagie Benaim, Lior Wolf
We consider the task of generating diverse and novel videos from a single video sample. Recently, new hierarchical patch-GAN based approaches were proposed for generating diverse i…