collaborators

5 papers

cs.CV2026

Scaling Laws in Patchification: An Image Is Worth 50,176 Tokens And More

Feng Wang, Yaodong Yu, Guoyizhe Wei +4

Since the introduction of Vision Transformer (ViT), patchification has long been regarded as a de facto image tokenization approach for plain visual architectures. By compressing t…

eess.IV2025

Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generation

Hongxu Jiang, Muhammad Imran, Teng Zhang +4

Denoising diffusion probabilistic models (DDPMs) have achieved unprecedented success in computer vision. However, they remain underutilized in medical imaging, a field crucial for…

cs.CV2025

Adventurer: Optimizing Vision Mamba Architecture Designs for Efficiency

Feng Wang, Timing Yang, Yaodong Yu +7

In this work, we introduce the Adventurer series models where we treat images as sequences of patch tokens and employ uni-directional language models to learn visual representation…

cs.CV2025

Mamba-R: Vision Mamba ALSO Needs Registers

Feng Wang, Jiahao Wang, Sucheng Ren +6

Similar to Vision Transformers, this paper identifies artifacts also present within the feature maps of Vision Mamba. These artifacts, corresponding to high-norm tokens emerging in…

eess.IV2025

Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge

Muhammad Imran, Jonathan R. Krebs, Vishal Balaji Sivaraman +60

Multi-class segmentation of the aorta in computed tomography angiography (CTA) scans is essential for diagnosing and planning complex endovascular treatments for patients with aort…