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FeaTok: Feature-Loss Tokenization for Image Generation

Xiaofeng, Zhang et al.
arXiv (All) · Papers
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computer-vision-and-pattern-recognition
Discrete image generators learn the distribution of tokens produced by an image tokenizer. These token representations should be easy for generators to model, not merely enable faithful image reconstruction. Yet these tokenizers are commonly trained to reconstruct pixels, which prioritizes low-level
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