SOURCE-LINKED INTELLIGENCE
AffineTok: Semantic Affine Consistency for Diffusion-Friendly Visual Tokenizer
Visual tokenizers increasingly inject semantic supervision into latent spaces to make downstream diffusion easier. Yet how these semantics should be organized to facilitate denoising remains underexplored. In this paper, we define the semantic recovery objective: the denoising process should recover the semantic content of the clean image from noisy latent, and a good tokenizer should make it easier. Existing approaches train a projector to predict the semantics directly from the noisy latent. We argue that this predicts the average of clean-image semantics, whereas what really needs to be ali
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-24T22:12:20.000Z
First collected: 2026-09-21T10:22:00.206Z. This is not the publication date.