30 open-source projects similar to implus/sknet, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best SKNet alternative.
Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"
This project is a collection of deep learning tools for image classification and audio tagging, providing a repository of pre-trained model weights and architectures. It serves as a Keras model zoo that enables the immediate use of established neural networks for inference and transfer learning. The library includes a music tagging framework that classifies audio recordings using convolutional recurrent neural networks and mel-spectrograms. For visual data, it provides implementations of architectures such as ResNet, VGG, and Xception, alongside a repository of weights trained on large datase
tensorrtx is a computer vision inference engine and model implementation library designed for graphics processor acceleration. It provides a framework for optimizing deep learning models through a GPU inference optimizer, a deep learning model converter for transforming weights from frameworks like TensorFlow and PyTorch, and a custom plugin library to implement operations not natively supported by the TensorRT API. The project distinguishes itself through a comprehensive collection of pre-defined network implementations, ranging from various YOLO versions and DETR transformers for object det
CNN architecture exploration using Genetic Algorithm
A repository for the code used to create and train the model defined in 'Context-aware Attentional Pooling (CAP) for Fine-grained Visual Classification' from AAAI 2021 (See the Paper section).
This repository is a PyTorch implementation of our coordinate attention (will appear in CVPR2021).
A PyTorch implementation of Mnasnet: MnasNet: Platform-Aware Neural Architecture Search for Mobile.
:fire::fire:A MXNet implementation of Modified CRUNet & Residual Attention Network:fire::fire:
:fire::fire: A MXNet implementation of Squeeze-and-Excitation Networks (SE-ResNext, SE-Resnet, SE-Inception-v4 and SE-Inception-Resnet-v2) :fire::fire:
PyTorch implementation of the paper "FcaNet: Frequency Channel Attention Networks".
The official PyTorch code implementation for TIP20' Submission: "Person Re-identification via Attention Pyramid"
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
This is a PyTorch implementation of CoAtNet specified in "CoAtNet: Marrying Convolution and Attention for All Data Sizes", arXiv 2021.
The PyTorch implementation of Att-DARTS: Differentiable Neural Architecture Search for Attention.
An implementation of the efficient attention module.
BiSeNetV2 is faster and requires less memory, you can try BiSeNetV2 on cityscapes like this: ` $ export CUDAVISIBLEDEVICES=0,1 $ python -m torch.distributed.launch --nprocpernode=2 bisenetv2/train.py --fp16 ` This would train the model and then compute the mIOU on eval set.
TensorFlow implementation of GoogLeNet and Inception for image classification.
This repository contains the code and trained models of "Sharing Residual Units Through Collective Tensor Factorization in Deep Neural Networks".
This project is built from IDN, and thanks for the contributions of all the other researchers those who made their codes accessible. paper_link:https://arxiv.org/ftp/arxiv/papers/2104/2104.07566.pdf
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters
PyTorch implementation of PNASNet-5 on ImageNet