A novel one-step diffusion model for human body restoration, efficiently handling human motion blur and generic noise in human images.

We propose BlurDM, a diffusion-based framework that integrates the physics of motion blur formation into the diffusion processes to improve image deblurring.

We present UniVF, a unified video fusion framework with multi-frame learning; VF-Bench, the first benchmark covering four video fusion tasks; and a unified spatial–temporal evaluation protocol with a new temporal consistency loss.

We present the first agent system for super-resolution that is capable of upscaling any image of arbitrary degradation to high-quality 4K resolution.