Hayk Manukyan — accepted AI-conference papers

2025

HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models

Hayk Manukyan, Andranik Sargsyan, Barsegh Atanyan, Zhangyang Wang, Shant Navasardyan, Humphrey Shi

ICLR 2025poster

Recent progress in text-guided image inpainting, based on the unprecedented success of text-to-image diffusion models, has led to exceptionally realistic and visually plausible results. However, there is still significant potential for improvement in current text-to-image inpainting models, particul…

Cited by 29 Source ↗PDF ↗code ↗Scholar ↗

2024

Zero-Painter: Training-Free Layout Control for Text-to-Image Synthesis

Marianna Ohanyan, Hayk Manukyan, Zhangyang Wang, Shant Navasardyan, Humphrey Shi

CVPR 2024poster

We present Zero-Painter a novel training-free framework for layout-conditional text-to-image synthesis that facilitates the creation of detailed and controlled imagery from textual prompts. Our method utilizes object masks and individual descriptions coupled with a global text prompt to generate ima…

Cited by 4 Source ↗PDF ↗code ↗Scholar ↗