2 citations · 3 across the 3 of their papers we have counts for
3 papers
Heeding the Inner Voice: Aligning ControlNet Training via Intermediate Features Feedback
Nina Konovalova, Maxim Nikolaev, Andrey Kuznetsov +1
Despite significant progress in text-to-image diffusion models, achieving precise spatial control over generated outputs remains challenging. ControlNet addresses this by introduci…
MaterialFusion: High-Quality, Zero-Shot, and Controllable Material Transfer with Diffusion Models
Kamil Garifullin, Maxim Nikolaev, Andrey Kuznetsov +1
Manipulating the material appearance of objects in images is critical for applications like augmented reality, virtual prototyping, and digital content creation. We present Materia…
HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach
Maxim Nikolaev, Mikhail Kuznetsov, Dmitry Vetrov +1
Our paper addresses the complex task of transferring a hairstyle from a reference image to an input photo for virtual hair try-on. This task is challenging due to the need to adapt…