vfm-visual-tokenizer

Use frozen vision foundation models like DINOv2 and CLIP as image tokenizers for autoregressive generation. Region-adaptive quantization identifies semantically coherent areas and reduces redundancy. Achieves 256-token encoding (vs. 576), 3× AR model speedup, state-of-the-art 1.36 gFID on ImageNet while eliminating classifier-free guidance.

Independent GitHub snapshot · Automated classification · Original documentation governs