4 papers
Vision Foundation Models as Generalist Tokenizers for Image Generation
Anlin Zheng, Qi Han, Xin Wen +5
In this work, we explore the largely unexplored direction of building a generalist image tokenizer directly on top of a frozen vision foundation model (VFM). To build this tokenize…
Vision Foundation Models as Effective Visual Tokenizers for Autoregressive Image Generation
Anlin Zheng, Xin Wen, Xuanyang Zhang +5
In this work, we present a novel direction to build an image tokenizer directly on top of a frozen vision foundation model, which is a largely underexplored area. Specifically, we…
Hita: Holistic Tokenizer for Autoregressive Image Generation
Anlin Zheng, Haochen Wang, Yucheng Zhao +4
Vanilla autoregressive image generation models generate visual tokens step-by-step, limiting their ability to capture holistic relationships among token sequences. Moreover, becaus…
Reconstructive Visual Instruction Tuning
Haochen Wang, Anlin Zheng, Yucheng Zhao +4
This paper introduces reconstructive visual instruction tuning (ROSS), a family of Large Multimodal Models (LMMs) that exploit vision-centric supervision signals. In contrast to co…