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Duc Vu

3 accepted papers

2026

InverFill: One-Step Inversion for Enhanced Few-Step Diffusion Inpainting

CVPR 2026

Recent diffusion-based models achieve photorealism in image inpainting but require many sampling steps, limiting practical use. Few-step text-to-image models offer faster generation, but naively applying them to inpainting yields poor harmonization and artifacts between the background and inpainted

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2025

Improved Training Technique for Shortcut Models

NeurIPS 2025poster

Shortcut models represent a promising, non-adversarial paradigm for generative modeling, uniquely supporting one-step, few-step, and multi-step sampling from a single trained network. However, their widespread adoption has been stymied by critical performance bottlenecks. This paper tackles the five…

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