AI RESEARCH
Mutual Enhancement Between Global Tokens and Patch Tokens: From Theory to Practice
arXiv CS.CV
•
ArXi:2605.16384v1 Announce Type: new Accurate and effective discrete image tokenization is crucial for long image sequence processing. However, current methods rigidly compress all content at a fixed rate, ignoring the variable information density of images and leading to either redundancy or information loss. Inspired by information entropy, we propose TaTok, a Theoretically grounded adaptive image Tokenization framework.