6 papers
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…
Express4D: Expressive, Friendly, and Extensible 4D Facial Motion Generation Benchmark
Yaron Aloni, Rotem Shalev-Arkushin, Yonatan Shafir +3
Dynamic facial expression generation from natural language is a crucial task in Computer Graphics, with applications in Animation, Virtual Avatars, and Human-Computer Interaction.…
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…
Towards AI-driven Sign Language Generation with Non-manual Markers
Han Zhang, Rotem Shalev-Arkushin, Vasileios Baltatzis +7
Sign languages are essential for the Deaf and Hard-of-Hearing (DHH) community. Sign language generation systems have the potential to support communication by translating from writ…
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…