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cs.CV2024
Inference Optimal VLMs Need Fewer Visual Tokens and More Parameters
Kevin Y. Li, Sachin Goyal, Joao D. Semedo +1
Vision Language Models (VLMs) have demonstrated strong capabilities across various visual understanding and reasoning tasks, driven by incorporating image representations into the…
cs.CV2021★ 2 cited
How to augment your ViTs? Consistency loss and StyleAug, a random style transfer augmentation
Akash Umakantha, Joao D. Semedo, S. Alireza Golestaneh +1
The Vision Transformer (ViT) architecture has recently achieved competitive performance across a variety of computer vision tasks. One of the motivations behind ViTs is weaker indu…