Ackesnal

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deit

Official DeiT repository

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dinov2

PyTorch code and models for the DINOv2 self-supervised learning method.

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dino

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

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TokenLabeling

Pytorch implementation of "All Tokens Matter: Token Labeling for Training Better Vision Transformers"

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Swin-Transformer

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

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EMO

Official PyTorch implementation of "Rethinking Mobile Block for Efficient Attention-based Models"

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mae

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

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GTP-ViT

This is the official code for paper: Token Summarisation for Efficient Vision Transformers via Graph-based Token Propagation

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DynamicViT

[NeurIPS 2021] DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification

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TokenReduction

Official PyTorch implementation of Which Tokens to Use? Investigating Token Reduction in Vision Transformers presented at ICCV 2023 NIVT workshop

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evit

Python code for ICLR 2022 spotlight paper EViT: Expediting Vision Transformers via Token Reorganizations

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mmsegmentation

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

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SegFormer

Official PyTorch implementation of SegFormer

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PEFD

[NeurIPS'22] Projector Ensemble Feature Distillation

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T2T-ViT

ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

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Robust-Vision-Transformer

The implementation of our paper: Towards Robust Vision Transformer (CVPR2022)

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volo

VOLO: Vision Outlooker for Visual Recognition

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releasing-research-code

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

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BossNAS

BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search

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CHoiCe-Dataset

A Cursive Handwriting Dataset with 62 classes and 40 photo for each

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bottom-up-attention

Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome

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ICCV19_VQA-CTI

Repo for our ICCV 19 paper: "Compact Trilinear Interaction for Visual Question Answering"

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