VTBench: Evaluating Visual Tokenizers for Autoregressive Image Generation
This study introduced VTBench to systematically evaluate Visual Tokenizers (VTs) used in autoregressive image generation models. It tested VTs across three tasks—Image Reconstruction, Detail Preservation, and Text Preservation—finding that discrete VTs fail to retain fine details and text integrity compared to continuous variational autoencoders.