Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
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Updated
Sep 10, 2024 - Python
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
This project aims to classify different types of fruits using deep learning. The objective is to build a model that can accurately identify the type of fruit based on images.
The MAMA-MIA Dataset: A Multi-Center Breast Cancer DCE-MRI Public Dataset with Expert Segmentations
Python script leveraging pre-trained ResNet18 for extracting video features from the YouTube Dataset, enabling LSTM-based action recognition models.
YOLOv3 implementation in TensorFlow 2.3.1
Pytorch implements yolov3.Good performance, easy to use, fast speed.
It is a comprehensive resource hub compiling all LLM papers accepted at the International Conference on Learning Representations (ICLR) in 2024.
Hierarchical Image Pyramid Transformer - CVPR 2022 (Oral)
Text To Motion Images With Diffusion Models
A c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: VGG, ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.
This repository contains an image classification model for the subject AI Convergence and Application held on Handong Global University (HGU)
EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation
The goal of this project is to devise an accurate CNN-based classifier able to distinguish between Cat and Dog in images where the animal is predominant.
I3D implemetation in Keras + video preprocessing + visualization of results
Pretrained TorchVision models on CIFAR10 dataset (with weights)
Tensorflow implementations of ConvNeXt V1 + V2 models w/ weights, including conversion and evaluation scripts.
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
Code for "Real-time self-adaptive deep stereo" - CVPR 2019 (ORAL)
PaddlePaddle image models, scripts, pretrained weights. Code was heavily based on timm.
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