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cs.CV2024
A Simple and Efficient Baseline for Zero-Shot Generative Classification
Zipeng Qi, Buhua Liu, Shiyan Zhang +4
Large diffusion models have become mainstream generative models in both academic studies and industrial AIGC applications. Recently, a number of works further explored how to emplo…
cs.CV2024
Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection
Lichen Bai, Shitong Shao, Zikai Zhou +4
Diffusion models, the most popular generative paradigm so far, can inject conditional information into the generation path to guide the latent towards desired directions. However,…
cs.CV2024
Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization
Zipeng Qi, Lichen Bai, Haoyi Xiong +1
Diffusion models that can generate high-quality data from randomly sampled Gaussian noises have become the mainstream generative method in both academia and industry. Are randomly…