Open-source alternatives to Vsepp

Classification with PyTorch.

Train an RL agent to execute natural language instructions in a 3D Environment (PyTorch)

A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks, https://arxiv.org/abs/1610.02915)

This is easy-to-follow Capsule Network tutorial with clean readable code: Capsule Network.ipynb

Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)

A PyTorch implementation of DenseNet.

Pixel-wise segmentation on the VOC2012dataset dataset using pytorchpytorch.

PyTorch implementation of Deformable Convolution

This is a PyTorch object detection framework that implements the Single Shot MultiBox Detector for identifying and localizing multiple objects within images and video. The project provides a neural network architecture designed for single-shot object detection, which predicts bounding boxes and class labels in one pass. The implementation includes a real-time object detector capable of processing live video streams to track and label objects across sequential frames. It also features a complete computer vision training pipeline for preparing image datasets and training model weights. The fra

PyTorch Implementation of Realtime Multi-Person Pose Estimation project.

This is a PyTorch-based computer vision library for detecting 2D and 3D facial landmark coordinates. It functions as a facial landmark detector and reconstruction tool, utilizing deep learning to identify precise geometric points on human faces from image datasets. The library allows for the selection of specific detection backends to balance accuracy and processing speed. It supports the integration of precomputed bounding box files, which enables the system to bypass the initial detection phase and proceed directly to landmark extraction. The toolkit includes capabilities for batch image p

This repo is implementation for PointNet(https://arxiv.org/abs/1612.00593) in pytorch. The model is in pointnet/model.py.

StackGAN-v1: Tensorflow implementation

This project is a computer vision explainable AI library and framework for PyTorch, providing a suite of tools to visualize and audit the internal decision-making processes of deep neural networks. It serves as a neural network attribution tool and debugging utility to identify which image regions drive model predictions. The library is distinguished by its support for both gradient-based and gradient-free attribution methods, allowing for the generation of visual heatmaps and attribution maps without requiring modifications to the original model source code. It further differentiates itself