2.3k citations · 2.5k across the 6 of their papers we have counts for
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cs.CV2022★ 2.3k cited
Hierarchical Text-Conditional Image Generation with CLIP Latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol +2
Contrastive models like CLIP have been shown to learn robust representations of images that capture both semantics and style. To leverage these representations for image generation…
cs.CV2017★ 153 cited
CycleGAN, a Master of Steganography
Casey Chu, Andrey Zhmoginov, Mark Sandler
CycleGAN (Zhu et al. 2017) is one recent successful approach to learn a transformation between two image distributions. In a series of experiments, we demonstrate an intriguing pro…