Bochen Guan — accepted AI-conference papers

2024

FreeControl: Training-Free Spatial Control of Any Text-to-Image Diffusion Model with Any Condition

Sicheng Mo, Fangzhou Mu, Kuan Heng Lin, Yanli Liu, Bochen Guan, Yin Li +1

CVPR 2024poster

Recent approaches such as ControlNet offer users fine-grained spatial control over text-to-image (T2I) diffusion models. However auxiliary modules have to be trained for each spatial condition type model architecture and checkpoint putting them at odds with the diverse intents and preferences a huma…

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2021

Spectral Domain Convolutional Neural Network

Bochen Guan, Jinnian Zhang, William A. Sethares, Richard Kijowski, Fang Liu

ICASSP 2021accepted

The memory consumption of most Convolutional Neural Network (CNN) architectures grows rapidly with increasing depth of the network, which is a major constraint for efficient network training on modern GPUs with limited memory, embedded systems, and mobile devices. Several studies show that the featu…

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