A treasure chest for visual classification and recognition powered by PaddlePaddle

PASSL包含 SimCLR，MoCo v1/v2，BYOL，CLIP，PixPro，simsiam, SwAV, BEiT，MAE 等图像自监督算法以及 Vision Transformer，DEiT，Swin Transformer，CvT，T2T-ViT，MLP-Mixer，XCiT，ConvNeXt，PVTv2 等基础视觉算法

HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision

Paddle Large Scale Classification Tools，supports ArcFace, CosFace, PartialFC, Data Parallel + Model Parallel. Model includes ResNet, ViT, Swin, DeiT, CaiT, FaceViT, MoCo, MAE, ConvMAE, CAE.

A PaddlePaddle version image model zoo.

(Unofficial) PyTorch implementation of Training Vision Transformers for Image Retrieval(El-Nouby, Alaaeldin, et al. 2021).

[CVPR 2024] Code for our Paper "DeiT-LT: Distillation Strikes Back for Vision Transformer training on Long-Tailed Datasets"

2D Human Pose estimation using transformers. Implementation in Pytorch

Pytorch implementation of some vision transformers, trained on CIFAR-10.

[CVPR'24] Once for Both: Single Stage of Importance and Sparsity Search for Vision Transformer Compression

Image Classification Tutorial: ConvNext--> 98.8% on CIFAR10 + 92.4% on CIFAR100; ResNet18 -- 95.6% on CIFAR10 + 79.1% on CIFAR100

This is a warehouse for DeiT-pytorch-model, can be used to train your image dataset

The analysis of several vision-based transformers is the main emphasis of this project, which also analyzes their distinctive properties and evaluates how well they work using a common dataset. The study intends to obtain insights into the strengths and shortcomings of various transformer designs created for computer vision tasks.

VisionTransformer for Tensorflow2

Final assignment in the NLP course at the Technion (IEM097215). In this assignment we propose a novel architecture to handle both Text-to-Image translation and Image-to-Text translation tasks on paired data, using a unified architecture of transformers and CNNs and enforcing cycle consistency.

This repository holds the downstream task of Face Mask Classification performed on Self Currated Custom Dataset with various State of the Art deep learning models like ViT, BeIT, DeIT, LeViT, ConvNeXt, VGG16, EfficientNetV2, RegNet and MobileNetV3.

Image classification with DeiT model, including data preprocessing, k-fold CV, early stopping and model saving.

"Neural Computing and Applications" Published Paper (2023)

Implementation of DeiT (Data-Efficient Image Transformer) for accurate and efficient brain stroke prediction using deep learning techniques.

Implementing a C++ API for alcohol consumption detection using transfer learning based DeIT model