Deep Compression/Acceleration（模型压缩加速总结）

根据个人理解将模型压缩方面研究分为以下七个方向：

结构structure

[CVPR2019] Searching for MobileNetV3

• intro: 神经网络结构搜索NAS 、强化学习
• arxiv: https://arxiv.org/abs/1905.02244
• github: https://github.com/xiaolai-sqlai/mobilenetv3
• github: https://github.com/leaderj1001/MobileNetV3-Pytorch

[BMVC2018] IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks

• intro:
• arxiv:https://arxiv.org/abs/1806.00178
• github:https://github.com/homles11/IGCV3

[CVPR2018] IGCV2: Interleaved Structured Sparse Convolutional Neural Networks

• intro:
• arxiv:https://arxiv.org/abs/1804.06202
• 同上

[CVPR2018] MobileNetV2: Inverted Residuals and Linear Bottlenecks

• intro:
• arxiv:https://arxiv.org/abs/1801.04381
• github:https://github.com/tensorflow/models/tree/master/research/slim/nets/mobilenet

[ECCV2018] ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

• intro:
• arxiv:https://arxiv.org/abs/1807.11164
• github:

量化quantization

Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

• intro:二值网络
• arxiv:https://arxiv.org/abs/1602.02830
• github: https://github.com/MatthieuCourbariaux/BinaryNet
  https://github.com/itayhubara/BinaryNet

[ACM2017] FINN: A Framework for Fast, Scalable Binarized Neural Network Inference

• intro:二值网络
• pdf:http://www.idi.ntnu.no/~yamanu/2017-fpga-finn-preprint.pdf
• github:https://github.com/Xilinx/FINN

[CVPR2016] DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

• intro:低bit位
• arxiv:https://arxiv.org/abs/1606.06160
• github:https://git