1 citations · 1 across the 6 of their papers we have counts for
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ImageRAG: Dynamic Image Retrieval for Reference-Guided Image Generation
Rotem Shalev-Arkushin, Rinon Gal, Amit H. Bermano +1
Diffusion models enable high-quality and diverse visual content synthesis. However, they struggle to generate rare or unseen concepts. To address this challenge, we explore the usa…
Monkey See, Monkey Do: Harnessing Self-attention in Motion Diffusion for Zero-shot Motion Transfer
Sigal Raab, Inbar Gat, Nathan Sala +5
Given the remarkable results of motion synthesis with diffusion models, a natural question arises: how can we effectively leverage these models for motion editing? Existing diffusi…
V-LASIK: Consistent Glasses-Removal from Videos Using Synthetic Data
Rotem Shalev-Arkushin, Aharon Azulay, Tavi Halperin +3
Diffusion-based generative models have recently shown remarkable image and video editing capabilities. However, local video editing, particularly removal of small attributes like g…
Ham2Pose: Animating Sign Language Notation into Pose Sequences
Rotem Shalev-Arkushin, Amit Moryossef, Ohad Fried
Translating spoken languages into Sign languages is necessary for open communication between the hearing and hearing-impaired communities. To achieve this goal, we propose the firs…