4 citations · 4 across the 6 of their papers we have counts for
6 papers · 1 filter
MultiAct: Text-to-Motion Generation from Composite Text via Tailored Attention Guidance
Nathan Sala, Ofir Abramovich, Ariel Shamir +3
Text-to-motion generation has progressed rapidly in recent years, offering an expressive interface for animation and human-computer interaction. However, current models remain brit…
Φ-Noise: Training-Free Temporal Video Conditioning via Phase-Based Noise Manipulation
Ofir Abramovich, Nadav Z. Cohen, Adi Rosenthal +1
Latent video diffusion models generate videos by progressively transforming Gaussian noise into realistic samples conditioned on text or visual inputs. However, existing conditioni…
Colorful-Noise: Training-Free Low-Frequency Noise Manipulation for Color-Based Conditional Image Generation
Nadav Z. Cohen, Ofir Abramovich, Ariel Shamir
Text-to-image diffusion models generate images by gradually converting white Gaussian noise into a natural image. White Gaussian noise is well suited for producing diverse outputs…
Mocap Anywhere: Towards Pairwise-Distance based Motion Capture in the Wild (for the Wild)
Ofir Abramovich, Ariel Shamir, Andreas Aristidou
We introduce a novel motion capture system that reconstructs full-body 3D motion using only sparse pairwise distance (PWD) measurements from body-mounted(UWB) sensors. Using time-o…
VisFocus: Prompt-Guided Vision Encoders for OCR-Free Dense Document Understanding
Ofir Abramovich, Niv Nayman, Sharon Fogel +7
In recent years, notable advancements have been made in the domain of visual document understanding, with the prevailing architecture comprising a cascade of vision and language mo…
PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers using Synthetic Scene Data
Roei Herzig, Ofir Abramovich, Elad Ben-Avraham +5
Action recognition models have achieved impressive results by incorporating scene-level annotations, such as objects, their relations, 3D structure, and more. However, obtaining an…