7 citations · 17 across the 8 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
RetinaRegNet: A Zero-Shot Approach for Retinal Image Registration
Vishal Balaji Sivaraman, Muhammad Imran, Qingyue Wei +7
We introduce RetinaRegNet, a zero-shot image registration model designed to register retinal images with minimal overlap, large deformations, and varying image quality. RetinaRegNe…
Unleashing the Potential of SAM for Medical Adaptation via Hierarchical Decoding
Zhiheng Cheng, Qingyue Wei, Hongru Zhu +4
The Segment Anything Model (SAM) has garnered significant attention for its versatile segmentation abilities and intuitive prompt-based interface. However, its application in medic…