- Learning Transferable Architectures for Scalable Image Recognition NASNet
- MnasNet: Platform-Aware Neural Architecture Search for Mobile MnasNet
- MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications MobileNets
- MobileNetV2: Inverted Residuals and Linear Bottlenecks MobileNetV2 MobileNetV2-pytorch
- MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks CVPR2018 code
- Searching for MobileNetV3 MobileNetV3 unofficial implementation MobileNetV3-for-Segmentation
- Efficient Net: Rethinking Model Scaling for Convolutional Neural Networks. ICML 2019 tfcode unofficial pytorch version
- Interleaved Group Convolutions for Deep Neural Networks IGCV
- IGCV2: Interleaved Structured Sparse Convolutional Neural Networks IGCV2
- IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks IGCV3
- Accelerating Deep Neural Networks with Spatial Bottleneck Modules arxiv2018
-
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution arxiv2019 unofficial implementation OctaveConv_pytorch OctaveConv_MXNet
-
FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search arxiv2018 code
-
ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation arxiv2018 code
- ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices ShuffleNet
- ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design ShuffleNet V2 Shufflenet-v2-Pytorch
- CondenseNet: An Efficient DenseNet using Learned Group Convolutions CondenseNet
- ANTNets: Mobile Convolutional Neural Networks for Resource Efficient Image Classification arxiv2019
- Seesaw-Net: Convolution Neural Network With Uneven Group Convolution arxiv2019
- ISBNet: Instance-aware Selective Branching Network arxiv2019
- Multinomial Distribution Learning for Effective Neural Architecture Search arxiv2019 code
- HGC: Hierarchical Group Convolution for Highly Efficient Neural Network arxiv2019
- DiCENet: Dimension-wise Convolutions for Efficient Networks arxiv2019 code
- Densely Connected Search Space for More Flexible Neural Architecture Search arxiv2019 code
-
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation ENet
-
ICNet for Real-Time Semantic Segmentation on High-Resolution Images ICNet
-
Speeding up Semantic Segmentation for Autonomous Driving SQNet
-
ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic Segmentation ERFNet
-
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation ESPNet
-
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation ECCV2018 code
-
A Comparative Study of Real-time Semantic Segmentation for Autonomous Driving
-
Efficient Dense Modules of Asymmetric Convolution for Real-Time Semantic Segmentation EDANet
-
Light-Weight RefineNet for Real-Time Semantic Segmentation Light-Weight RefineNet
-
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction
-
CGNet: A Light-weight Context Guided Network for Semantic Segmentation arxiv2018 code
-
Concentrated-Comprehensive Convolutions for lightweight semantic segmentation arxiv2018
-
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network arxiv2018 code
-
Fast-SCNN: Fast Semantic Segmentation Network arxiv2019 code blog
-
An efficient solution for semantic segmentation: ShuffleNet V2 with atrous separable convolutions arxiv2019
-
Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation cvpr2019
-
DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation cvpr2019Megvii
-
Real time backbone for semantic segmentation arxiv2019
-
Residual Pyramid Learning for Single-Shot Semantic Segmentation arxiv2019
-
Knowledge Adaptation for Efficient Semantic Segmentation cvpr2019
-
In Defense of Pre-trained ImageNet Architectures for Real-time Semantic Segmentation of Road-driving Imagescvpr2019 code
-
Towards Real-Time Automatic Portrait Matting on Mobile Devices arxiv2019 code
-
PortraitNet: Real-time Portrait Segmentation Network for Mobile Device Computers & Graphics 2019 code
-
Design of Real-time Semantic Segmentation Decoder for Automated Driving VISAPP2019
-
ThunderNet: A Turbo Unified Network for Real-Time Semantic Segmentation WACV2019
-
LEDNet: A Lightweight Encoder-Decoder Network for Real-time Semantic Segmentation ICIP2019 code
-
Accurate Facial Image Parsing at Real-Time Speed TIP2019
-
Efficient Ladder-style DenseNets for Semantic Segmentation of Large Images arxiv2019
-
Nail Polish Try-On: Realtime Semantic Segmentation of Small Objects forNative and Browser Smartphone AR Applications CVPRW2019
-
ESNet: An Efficient Symmetric Network for Real-time Semantic Segmentation arxiv2019 code
-
Real-time Hair Segmentation and Recoloring on Mobile GPUs 2019CVPRW
-
PC-DARTS: Partial Channel Connections for Memory-Efficient Differentiable Architecture Search arxiv2019 code Shanghai Jiao Tong University&&Huawei
-
Densely Connected Search Space for More Flexible Neural Architecture Search arxiv2019 code Huazhong University of Science and Technology &&Horizon Robotics
-
FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search arxiv2019 code Xiaomi AI Lab
- A Recipe for Training Neural Networks (Apr 25, 2019)
- Improving deep learning models with bag of tricks (Dec 13,2018)
- A Bag of Tricks for Image Classification (Dec 17, 2018)
- Bag of Tricks for Image Classification with Convolutional Neural Networks cvpr2019 code
- Bag of Freebies for Training Object Detection Neural Networks arxiv2019 code
- Awesome-model-compression-and-acceleration
- awesome-model-compression-and-acceleration
- Model-Compression-Papers
- Awesome-model-compression-and-acceleration
- awesome-AutoML-and-Lightweight-Models
- 常用的语义分割架构结构综述以及代码复现
- Real-time Portrait Segmentation on Smartphones
- Mobile Real-time Video Segmentation
- Real-Time deep learning in mobile application
- QNNPACK: Open source library for optimized mobile deep learning
- 第十七章 模型压缩及移动端部署
- Tips for building fast portrait segmentation network with TensorFlow Lite
- Literature On Neural network architecture