210 citations · 984 across the 29 of their papers we have counts for
5 papers · 1 filter
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…
Conditional Balance: Improving Multi-Conditioning Trade-Offs in Image Generation
Nadav Z. Cohen, Oron Nir, Ariel Shamir
Balancing content fidelity and artistic style is a pivotal challenge in image generation. While traditional style transfer methods and modern Denoising Diffusion Probabilistic Mode…
Semantic Segmentation in Art Paintings
Nadav Cohen, Yael Newman, Ariel Shamir
Semantic segmentation is a difficult task even when trained in a supervised manner on photographs. In this paper, we tackle the problem of semantic segmentation of artistic paintin…
"Zero-Shot" Super-Resolution using Deep Internal Learning
Assaf Shocher, Nadav Cohen, Michal Irani
Deep Learning has led to a dramatic leap in Super-Resolution (SR) performance in the past few years. However, being supervised, these SR methods are restricted to specific training…