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pro vyhledávání: '"Courdier, Evann"'
Autoregressive models, such as the GPT family, use a fixed order, usually left-to-right, to generate sequences. However, this is not a necessity. In this paper, we challenge this assumption and show that by simply adding a positional encoding for the
Externí odkaz:
http://arxiv.org/abs/2404.09562
We study the problem of improving the efficiency of segmentation transformers by using disparate amounts of computation for different parts of the image. Our method, PAUMER, accomplishes this by pausing computation for patches that are deemed to not
Externí odkaz:
http://arxiv.org/abs/2311.00586
Autor:
Courdier, Evann, Fleuret, François
Semantic segmentation is a well-addressed topic in the computer vision literature, but the design of fast and accurate video processing networks remains challenging. In addition, to run on embedded hardware, computer vision models often have to make
Externí odkaz:
http://arxiv.org/abs/2202.05748
Autor:
Courdier, Evann, Fleuret, Francois
As scene segmentation systems reach visually accurate results, many recent papers focus on making these network architectures faster, smaller and more efficient. In particular, studies often aim at designingreal-time'systems. Achieving this goal is p
Externí odkaz:
http://arxiv.org/abs/2004.02574