efficient-inference

There are 2 repositories under efficient-inference topic.

huawei-noah / Efficient-AI-Backbones
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
convolutional-neural-networks efficient-inference imagenet model-compression tensorflow pytorch ghostnet transformer pretrained-models vision-transformer
Language:Python 2400
huawei-noah / AdderNet
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
pytorch imagenet convolutional-neural-networks cvpr2020 efficient-inference
Language:Python 891
liuzhuang13 / slimming
Learning Efficient Convolutional Networks through Network Slimming, In ICCV 2017.
deep-learning convolutional-neural-networks efficient-inference
Language:Lua 485
The-Learning-And-Vision-Atelier-LAVA / SMSR
[CVPR 2021] Exploring Sparsity in Image Super-Resolution for Efficient Inference
super-resolution sparsity efficient-inference
Language:Python 206
liuziwei7 / mobile-id
Deep Face Model Compression
computer-vision deep-learning face-recognition model-compression efficient-inference
Language:MATLAB 191
changlin31 / DS-Net
(CVPR 2021, Oral) Dynamic Slimmable Network
dynamic-networks pruning network-pruning dynamic-pruning model-compression efficient-inference
Language:Python 183
RAIVNLab / STR
Soft Threshold Weight Reparameterization for Learnable Sparsity
sparsity learnable-sparsity sparsity-optimization cnn efficient-inference edge-machine-learning soft-thresholding str imagenet resource-efficient icml-2020 icml icml2020 soft-threshold-reparameterization
Language:Python 67
cure-lab / DeciWatch
This is an official implementation for "DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation"
2d-human-pose 3d-pose-estimation body-reconstruction efficient-inference human-pose-estimation 3d-body-recovery deep-learning efficiency efficient-neural-networks pose-estimation pytorch
Language:Python 46
FranxYao / Partially-Observed-TreeCRFs
Implementation of AAAI 21 paper: Nested Named Entity Recognition with Partially Observed TreeCRFs
crf named-entity-recognition efficient-inference nested-named-entity-recognition tree-crf tree-structure sum-product-algorithm sum-product
Language:Python 45
ivclab / agegenderLMTCNN
Jia-Hong Lee, Yi-Ming Chan, Ting-Yen Chen, and Chu-Song Chen, "Joint Estimation of Age and Gender from Unconstrained Face Images using Lightweight Multi-task CNN for Mobile Applications," IEEE International Conference on Multimedia Information Processing and Retrieval, MIPR 2018
age-gender-cnn mobile-application multi-task-learning tensorflow android-application efficient-inference deep-neural-networks
Language:Python 39
IBM / AdaMML
Official implementation of AdaMML. https://arxiv.org/abs/2105.05165.
computer-vision multimodal-learning deep-learning efficient-inference
Language:Python 38
yikaiw / RS-Nets
[ECCV 2020] Code release for "Resolution Switchable Networks for Runtime Efficient Image Recognition"
eccv2020 rsnet multi-resolution ensemble distillation quantization efficient-inference switchable
Language:Python 36
linksense / EfficientNet.PyTorch
Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights.
efficientnet efficient-model efficient-inference pytorch efficientnet-pytorch efficientnet-pretrained efficientseg imagenet pretrained-weights
Language:Python 27
VITA-Group / triple-wins
[ICLR 2020] ”Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference“
adversarial-robustness adversarial-attacks triple-wins efficiency robustness efficient-inference
Language:Python 22
ivclab / NeuralMerger
Yi-Min Chou, Yi-Ming Chan, Jia-Hong Lee, Chih-Yi Chiu, Chu-Song Chen, "Unifying and Merging Well-trained Deep Neural Networks for Inference Stage," International Joint Conference on Artificial Intelligence (IJCAI), 2018
deep-neural-networks multi-task-learning cnn-compression unifying-and-merging-cnn efficient-inference tensorflow multi-modal-learning
Language:Python 20
Zhen-Dong / Awesome-Quantization-Papers
List of papers related to neural network quantization in recent AI conferences and journals (please refer to README in the folder for a better view).
quantization awesome-list papers neural-networks model-compression edge-computing efficient-inference
19
bharathsudharsan / CNN_on_MCU
Code for paper: 'Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT Hardware'
c-code-generator cmsis-nn edge-computing efficient-inference graph-optimization neuralnetworks optimization quantization quantization-aware-training tflite tflite-conversion tinyml
Language:Jupyter Notebook 18
Zhen-Dong / CoDeNet
[FPGA'21] CoDeNet is an efficient object detection model on PyTorch, with SOTA performance on VOC and COCO based on CenterNet and Co-Designed deformable convolution.
fpgas pretrained-models quantization deformable-convnets centernet pytorch efficient-inference detector efficient object-detection
Language:Python 17
xternalz / SDPoint
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
convolutional-networks resnets resnet efficient-inference pooling downsampling convolutional-neural-networks efficient-model deep-neural-networks deep-learning deep-learning-algorithms computer-vision regularization cost-adjustable resnext preact-resnet imagenet imagenet-dataset batch-normalization batchnorm
Language:Python 16
ivclab / Multistage_Pruning
Cheng-Hao Tu, Jia-Hong Lee, Yi-Ming Chan and Chu-Song Chen, "Pruning Depthwise Separable Convolutions for MobileNet Compression," International Joint Conference on Neural Networks, IJCNN 2020, July 2020.
pytorch network-pruning deep-neural-networks filter-pruning channel-pruning mobilenet depthwise-separable-convolutions model-compression efficient-inference
Language:Python 14
bharathsudharsan / ML-Classifiers-on-MCUs
Supplementary material for IEEE Services Computing paper title 'An SRAM Optimized Approach for Constant Memory Consumption and Ultra-fast Execution of ML Classifiers on TinyML Hardware'
adafruit-feather arduino arm-cortex-m0 code-generation decision-tree-classifier efficient-inference esp32 microcontroller optimization random-forest-classifier stm32 tinyml
Language:Jupyter Notebook 13
bharathsudharsan / TinyML-Benchmark-NNs-on-MCUs
Repo of paper: TinyML Benchmark: Executing Fully Connected Neural Networks on Commodity Microcontrollers
arduinio armcortexm0 armcortexm4 armcortexm7 c-code-generator cmsis-nn efficient-inference machine-learning mcu-boards raspberry-pi-pico tflite tfmicro tinyml tinyml-benchmark
Language:Python 11
ivclab / Merging-MobileNets-for-Multitask
Cheng-En Wu, Yi-Ming Chan and Chu-Song Chen "On Merging MobileNets for Efficient Multitask Inference", International Symposium on High-Performance Computer Architecture(HPCA) on Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications(EMC2), 2019
deep-neural-networks multi-task-learning mobilenet efficient-inference tensorflow
Language:Python 10
d-becking / efficientCNNs
Finding Storage- and Compute-Efficient Convolutional Neural Networks
micronet-challenge compound-scaling quantization sparsity efficient-inference pytorch neural-network neural-architecture-search entropy-coding efficient-neural-networks ec2t sparsity-optimization quantization-algorithms
Language:Python 6
HolmesShuan / PyTorch-MixNet-SS
Extremely light-weight MixNet with Top-1 75.7% and 2.5M params
deep-neural-networks mixnet image-classification efficientnet efficient-inference efficient-model pytorch pretrained-models
Language:Python 6
neurips-2019-micronet-challenge
d-becking / neurips-2019-micronet-challenge
NeurIPS 2019 MicroNet Challenge
micronet-challenge efficient-neural-networks compound-scaling quantization quantization-algorithms sparsity sparsity-optimization efficient-inference pytorch neural-network neural-architecture-search entropy-coding ec2t
Language:Python 5
bharathsudharsan / Edge2Train
Code for paper: 'Edge2Train: a framework to train machine learning models (SVMs) on resource-constrained IoT edge devices'
arm-cortex-m0 arm-cortex-m4 edge-computing efficient-inference iot-devices microcontroller online-learning optimization svm-training tinyml
Language:C 3
megh1241 / blockset
BLOCKSET: Efficient out of core tree ensemble inference
gradient-boosting random-forest tree-ensemble efficient-inference aws-lambda on-device-ai out-of-core machine-learning memory-efficient
Language:C++ 3
tilmto / Adjustable-Quantization-MicroNet
[MicroNet Challenge (NeurIPS 2019 )] "Adjustable Quantization: Jointly Learn the Bit-width and Weight in DNN Training" by Yonggan Fu, Ruiyang Zhao, Yue Wang, Chaojian Li, Haoran You, Zhangyang Wang, Yingyan Lin
tensorflow quantization learnable-quantizer efficient-inference
Language:Python 3
bharathsudharsan / ECML-Tutorial-ML-Meets-IoT
Repository of the ECML PKDD 2021 tutorial title 'Machine Learning Meets Internet of Things: From Theory to Practice'
arm-cortex-m0 arm-cortex-m4 cmsis-nn edge-computing efficient-inference graph-optimization iot-devices machine-learning optimization pruning quantization self-learning tflite tinyml training-algorithms
Language:Jupyter Notebook 2
HarriBellThomas / VDQN
Exploring Variational Deep Q Networks. A study undertaken for the University of Cambridge's R244 Computer Science Masters Course. Inspired by https://arxiv.org/abs/1711.11225/.
qlearning variational-inference machine-learning ai efficient-model efficient-inference dqn ddqn vdqn dvdqn
Language:Python 2
twcmchang / CP-CNN
Channel-Prioritized Convolutional Neural Networks for Sparsity and Multi-fidelity
compression-algorithm convolutional-neural-networks network-pruning efficient-inference
Language:Python 2
maxwells-daemons / genome
Compute-efficient reinforcement learning with binary neural networks and evolution strategies.
reinforcement-learning openai-gym python cython evolutionary-algorithms efficient-inference
Language:Python 1
saife245 / IMAGE-RECOGNATION
image-recognition image-classification computer-vision ai image-processing kaggle-competition imagenet noisy-student efficient-inference efficientnet
Language:Jupyter Notebook 1
Ahmad-Shawahna / FxP-QNet
A Post-Training Quantizer for the Design of Mixed Low-Precision DNNs with Dynamic Fixed-Point Representation for Efficient Hardware Acceleration on Edge Devices
neural-networks model-compression deep-learning quantization fixed-point-arithmetic mixed-precision acceleration accuracy efficient-inference resource-constrained-devices
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