2 citations · 3 across the 3 of their papers we have counts for
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cs.CV2024
ByteEdit: Boost, Comply and Accelerate Generative Image Editing
Yuxi Ren, Jie Wu, Yanzuo Lu +11
Recent advancements in diffusion-based generative image editing have sparked a profound revolution, reshaping the landscape of image outpainting and inpainting tasks. Despite these…
cs.CV2023
AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Acceleration
Lijiang Li, Huixia Li, Xiawu Zheng +7
Diffusion models are emerging expressive generative models, in which a large number of time steps (inference steps) are required for a single image generation. To accelerate such t…
cs.CV2023★ 2 cited
DLIP: Distilling Language-Image Pre-training
Huafeng Kuang, Jie Wu, Xiawu Zheng +5
Vision-Language Pre-training (VLP) shows remarkable progress with the assistance of extremely heavy parameters, which challenges deployment in real applications. Knowledge distilla…