snap-research/EfficientFormer

EfficientFormerV2 [ICCV 2023] & EfficientFormer [NeurIPs 2022]

PythonShelldeep-learningdetectiontransformerspytorchtransformerimagenetsemantic-segmentationmobile-devicesefficient-inferenceefficient-neural-networks
This is stars and forks stats for /snap-research/EfficientFormer repository. As of 06 May, 2024 this repository has 846 stars and 84 forks.

EfficientFormerV2Rethinking Vision Transformers for MobileNet Size and Speed arXiv | PDF Models are trained on ImageNet-1K and deployed on iPhone 12 with CoreMLTools to get latency. Rethinking Vision Transformers for MobileNet Size and Speed Yanyu Li1,2, Ju Hu1, Yang Wen1, Georgios Evangelidis1, Kamyar Salahi3, Yanzhi Wang2, Sergey Tulyakov1, Jian Ren1 1Snap Inc., 2Northeastern University, 3UC Berkeley Abstract With the success of Vision Transformers (ViTs) in computer vision tasks,...
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