Stars
Famous Vision Language Models and Their Architectures
Paddle Multimodal Integration and eXploration, supporting mainstream multi-modal tasks, including end-to-end large-scale multi-modal pretrain models and diffusion model toolbox. Equipped with high …
Ongoing research training transformer models at scale
End-to-End Object Detection with Transformers
Awesome papers about Multi-Camera 3D Object Detection and Segmentation in Bird's-Eye-View, such as DETR3D, BEVDet, BEVFormer, BEVDepth, UniAD
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
Simple Waymo Open Dataset Reader
A 3D computer vision development toolkit based on PaddlePaddle. It supports point-cloud object detection, segmentation, and monocular 3D object detection models.
Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image …
Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.
Fall Detection using OpenPifPaf's Human Pose Estimation model
Fall Detection video dataset. A new processed dataset here.
Real-time fall detection using two-stream convolutional neural net (CNN) with Motion History Image (MHI)
SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection
Most popular metrics used to evaluate object detection algorithms.
MobileNetV1, MobileNetV2, VGG based SSD/SSD-lite implementation in Pytorch 1.0 / Pytorch 0.4. Out-of-box support for retraining on Open Images dataset. ONNX and Caffe2 support. Experiment Ideas lik…
This repository contains the codebase mentioned and used in trains' blogs
experiments on Paper <Bag of Tricks for Image Classification with Convolutional Neural Networks> and other useful tricks to improve CNN acc
Tiny-ImageNet Classifier using Pytorch
model learning and test for tiny-imageNet
Pretrained TorchVision models on CIFAR10 dataset (with weights)
Pretrained models on CIFAR10/100 in PyTorch
Pytorch implementation of convolutional neural network visualization techniques