5 papers
Griffin: Generative Reference and Layout Guided Image Composition
Aryan Mikaeili, Amirhossein Alimohammadi, Negar Hassanpour +2
Text-to-image models have achieved a level of realism that enables the generation of highly convincing images. However, text-based control can be a limiting factor when more explic…
Cora: Correspondence-aware image editing using few step diffusion
Amirhossein Alimohammadi, Aryan Mikaeili, Sauradip Nag +3
Image editing is an important task in computer graphics, vision, and VFX, with recent diffusion-based methods achieving fast and high-quality results. However, edits requiring sign…
Fantastic Multi-Task Gradient Updates and How to Find Them In a Cone
Negar Hassanpour, Muhammad Kamran Janjua, Kunlin Zhang +4
Balancing competing objectives remains a fundamental challenge in multi-task learning (MTL), primarily due to conflicting gradients across individual tasks. A common solution relie…
PixelMan: Consistent Object Editing with Diffusion Models via Pixel Manipulation and Generation
Liyao Jiang, Negar Hassanpour, Mohammad Salameh +4
Recent research explores the potential of Diffusion Models (DMs) for consistent object editing, which aims to modify object position, size, and composition, etc., while preserving…
QuaSeDiMo: Quantifiable Quantization Sensitivity of Diffusion Models
Keith G. Mills, Mohammad Salameh, Ruichen Chen +3
Diffusion Models (DM) have democratized AI image generation through an iterative denoising process. Quantization is a major technique to alleviate the inference cost and reduce the…