3 papers
cs.CV2025
Alchemist: Turning Public Text-to-Image Data into Generative Gold
Valerii Startsev, Alexander Ustyuzhanin, Alexey Kirillov +2
Pre-training equips text-to-image (T2I) models with broad world knowledge, but this alone is often insufficient to achieve high aesthetic quality and alignment. Consequently, super…
cs.CV2024
IQA-Adapter: Exploring Knowledge Transfer from Image Quality Assessment to Diffusion-based Generative Models
Khaled Abud, Sergey Lavrushkin, Alexey Kirillov +1
Diffusion-based models have recently revolutionized image generation, achieving unprecedented levels of fidelity. However, consistent generation of high-quality images remains chal…
cs.CV2024
YaART: Yet Another ART Rendering Technology
Sergey Kastryulin, Artem Konev, Alexander Shishenya +20
In the rapidly progressing field of generative models, the development of efficient and high-fidelity text-to-image diffusion systems represents a significant frontier. This study…