5 papers
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…
Ross3D: Reconstructive Visual Instruction Tuning with 3D-Awareness
Haochen Wang, Yucheng Zhao, Tiancai Wang +3
The rapid development of Large Multimodal Models (LMMs) for 2D images and videos has spurred efforts to adapt these models for interpreting 3D scenes. However, the absence of large…
Neighboring Slice Noise2Noise: Self-Supervised Medical Image Denoising from Single Noisy Image Volume
Langrui Zhou, Ziteng Zhou, Xinyu Huang +3
In the last few years, with the rapid development of deep learning technologies, supervised methods based on convolutional neural networks have greatly enhanced the performance of…
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…