Lornatang/SRCNN-PyTorch
Pytorch framework can easily implement srcnn algorithm with excellent performance
I like to use AI to do whatever I want
Pytorch framework can easily implement srcnn algorithm with excellent performance
An PyTorch implementation AlexNet.Simple, easy to use and efficient
PyTorch implements "Accurate Image Super-Resolution Using Very Deep Convolutional Networks"
A simple and complete implementation of super-resolution paper.
Open-source evaluation toolkit of large multi-modality models (LMMs), support 220+ LMMs, 80+ benchmarks
Fast implementation of fsrcnn algorithm based on pytorch framework
MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.
A PyTorch implementation of ESPCN based on CVPR 2016 paper Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network.
PyTorch implemnts `An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition` paper.
Improved training of Wasserstein GANs
A simple implementation of esrgan, which uses the pytorch framework.
PyTorch implements `Designing a Practical Degradation Model for Deep Blind Image Super-Resolution` paper.
The implementation of VGG thesis is implemented under PyTorch framework
PyTorch implements `Wide Residual Networks` paper.
PyTorch implements `MobileNetV2: Inverted Residuals and Linear Bottlenecks` paper.
LLM inference in C/C++
Pytorch implements yolov4.Good performance, easy to use, fast speed.
One-for-All Multimodal Evaluation Toolkit Across Text, Image, Video, and Audio Tasks
PyTorch implements `Deep Residual Learning for Image Recognition` paper.
PyTorch implements Auxiliary Classifier GAN
PyTorch implements `Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data` paper.
C语言考试复习资料
PyTorch implements StackGAN
Simple implementation of conditional general adverse nets in pytorch machine learning framework
PyTorch implements "Image Super-Resolution via Deep Recursive Residual Network"
Pytorch implements yolov3.Good performance, easy to use, fast speed.
Cifar100 in alexnet network model under the highest accuracy
PyTorch implements `Xception: Deep Learning with Depthwise Separable Convolutions` paper.
PyTorch implements `MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications` paper.
PyTorch implements `RepVGG: Making VGG-style ConvNets Great Again` paper.