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Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios. (arXiv:2207.05501v4 [cs.CV] UPDATED)
Aug. 17, 2022, 1:12 a.m. | Jiashi Li, Xin Xia, Wei Li, Huixia Li, Xing Wang, Xuefeng Xiao, Rui Wang, Min Zheng, Xin Pan
cs.CV updates on arXiv.org arxiv.org
Due to the complex attention mechanisms and model design, most existing
vision Transformers (ViTs) can not perform as efficiently as convolutional
neural networks (CNNs) in realistic industrial deployment scenarios, e.g.
TensorRT and CoreML. This poses a distinct challenge: Can a visual neural
network be designed to infer as fast as CNNs and perform as powerful as ViTs?
Recent works have tried to design CNN-Transformer hybrid architectures to
address this issue, yet the overall performance of these works is far away …
arxiv cv deployment generation industrial transformer vision
More from arxiv.org / cs.CV updates on arXiv.org
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