14 citations · 29 across the 10 of their papers we have counts for
11 papers
Contrastive Sequential-Diffusion Learning: Non-linear and Multi-Scene Instructional Video Synthesis
Vasco Ramos, Yonatan Bitton, Michal Yarom +2
Generated video scenes for action-centric sequence descriptions, such as recipe instructions and do-it-yourself projects, often include non-linear patterns, where the next video ma…
VideoPhy: Evaluating Physical Commonsense for Video Generation
Hritik Bansal, Zongyu Lin, Tianyi Xie +7
Recent advances in internet-scale video data pretraining have led to the development of text-to-video generative models that can create high-quality videos across a broad range of…
Generating Coherent Sequences of Visual Illustrations for Real-World Manual Tasks
João Bordalo, Vasco Ramos, Rodrigo Valério +5
Multistep instructions, such as recipes and how-to guides, greatly benefit from visual aids, such as a series of images that accompany the instruction steps. While Large Language M…
TALC: Time-Aligned Captions for Multi-Scene Text-to-Video Generation
Hritik Bansal, Yonatan Bitton, Michal Yarom +3
Most of these text-to-video (T2V) generative models often produce single-scene video clips that depict an entity performing a particular action (e.g., 'a red panda climbing a tree'…
Transferring Visual Attributes from Natural Language to Verified Image Generation
Rodrigo Valerio, Joao Bordalo, Michal Yarom +3
Text to image generation methods (T2I) are widely popular in generating art and other creative artifacts. While visual hallucinations can be a positive factor in scenarios where cr…
What You See is What You Read? Improving Text-Image Alignment Evaluation
Michal Yarom, Yonatan Bitton, Soravit Changpinyo +5
Automatically determining whether a text and a corresponding image are semantically aligned is a significant challenge for vision-language models, with applications in generative t…
MyStyle: A Personalized Generative Prior
Yotam Nitzan, Kfir Aberman, Qiurui He +6
We introduce MyStyle, a personalized deep generative prior trained with a few shots of an individual. MyStyle allows to reconstruct, enhance and edit images of a specific person, s…
Self-Distilled StyleGAN: Towards Generation from Internet Photos
Ron Mokady, Michal Yarom, Omer Tov +5
StyleGAN is known to produce high-fidelity images, while also offering unprecedented semantic editing. However, these fascinating abilities have been demonstrated only on a limited…
Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Oran Lang, Yossi Gandelsman, Michal Yarom +8
Image classification models can depend on multiple different semantic attributes of the image. An explanation of the decision of the classifier needs to both discover and visualize…
Semantic Pyramid for Image Generation
Assaf Shocher, Yossi Gandelsman, Inbar Mosseri +4
We present a novel GAN-based model that utilizes the space of deep features learned by a pre-trained classification model. Inspired by classical image pyramid representations, we c…
Temporal-Needle: A view and appearance invariant video descriptor
Michal Yarom, Michal Irani
The ability to detect similar actions across videos can be very useful for real-world applications in many fields. However, this task is still challenging for existing systems, sin…