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cs.CV2026

MOSAIK: Multi-Patch Content-Aware Spatial Allocation of Image Tokens for Efficient Generation

Mohammadreza Hami, Mohammadreza Samadi, Chao Gao +1

Pixel-space diffusion models avoid the reconstruction ceiling of latent diffusion models by generating directly in image space. However, their substantially higher token count make…

cs.CV2025

RePack then Refine: Efficient Diffusion Transformer with Vision Foundation Model

Guanfang Dong, Luke Schultz, Negar Hassanpour +1

Semantic-rich features from Vision Foundation Models (VFMs) have been leveraged to enhance Latent Diffusion Models (LDMs). However, raw VFM features are typically high-dimensional…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2024

FRAP: Faithful and Realistic Text-to-Image Generation with Adaptive Prompt Weighting

Liyao Jiang, Negar Hassanpour, Mohammad Salameh +4

Text-to-image (T2I) diffusion models have demonstrated impressive capabilities in generating high-quality images given a text prompt. However, ensuring the prompt-image alignment r…