activity
20192022
most citedHierarchical Patch VAE-GAN: Generating Diverse Videos from a Single Sample

12 citations · 34 across the 10 of their papers we have counts for

collaborators

12 papers

cs.LG2022★ 4 cited

Neural Inverse Kinematics

Raphael Bensadoun, Shir Gur, Nitsan Blau +2

Inverse kinematic (IK) methods recover the parameters of the joints, given the desired position of selected elements in the kinematic chain. While the problem is well-defined and l…

cs.LG2022★ 1 cited

Unsupervised Disentanglement with Tensor Product Representations on the Torus

Michael Rotman, Amit Dekel, Shir Gur +2

The current methods for learning representations with auto-encoders almost exclusively employ vectors as the latent representations. In this work, we propose to employ a tensor pro…

cs.CV2021

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…

cs.CV2021

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,…

cs.CV2021★ 3 cited

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…

cs.CV2020★ 5 cited

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…

cs.CV2020

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.…

cs.CV2020★ 12 cited

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…

eess.IV2020

Microvascular Dynamics from 4D Microscopy Using Temporal Segmentation

Shir Gur, Lior Wolf, Lior Golgher +1

Recently developed methods for rapid continuous volumetric two-photon microscopy facilitate the observation of neuronal activity in hundreds of individual neurons and changes in bl…

cs.CV2020★ 2 cited

Single Image Depth Estimation Trained via Depth from Defocus Cues

Shir Gur, Lior Wolf

Estimating depth from a single RGB images is a fundamental task in computer vision, which is most directly solved using supervised deep learning. In the field of unsupervised learn…

cs.CV2019★ 7 cited

End to End Trainable Active Contours via Differentiable Rendering

Shir Gur, Tal Shaharabany, Lior Wolf

We present an image segmentation method that iteratively evolves a polygon. At each iteration, the vertices of the polygon are displaced based on the local value of a 2D shift map…

eess.IV2019

Unsupervised Microvascular Image Segmentation Using an Active Contours Mimicking Neural Network

Shir Gur, Lior Wolf, Lior Golgher +1

The task of blood vessel segmentation in microscopy images is crucial for many diagnostic and research applications. However, vessels can look vastly different, depending on the tr…