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Research Direction 01

Generative & Restoration AI

Generative and Restoration AI research

We study modern generative models including diffusion models, GAN variants, and recent video and 3D/4D generative frameworks. Our research emphasizes controllable generation, temporal and spatial consistency, efficient inference, and safety. We aim to build practical generative pipelines that can reliably produce high-quality images, videos, and 3D/4D representations under real-world computational and deployment constraints.

Research Topics

Diffusion Models Video Generation 3D / 4D Generation Controllable Generation Efficient Inference Safe & Trustworthy Generation