A treasure chest for visual classification and recognition powered by PaddlePaddle
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Updated
Oct 27, 2025 - Python
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
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"
[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
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.
Swin Transformer + DETR, applied distillation queries & hard-level distillation
Image captioning with pretrained encoder on MSCOCO.
"Neural Computing and Applications" Published Paper (2023)
Implementation of a Paper related to Vision Transformer
This is a warehouse for Agent-Attention-Models based on pytorch framework, can be used to train your image datasets.
This is a warehouse for SBCFormer-pytorch-model, can be used to train your dataset
Proyek perbandingan performa dua model Vision Transformer (Swin Transformer dan DeiT) pada dataset Indonesian Food Classification dengan 5 kelas.
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