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Search results for python masked image modeling

masked-image-modeling x

19 search results found

Spark ⭐ 1,355

[ICLR'23 Spotlight🔥] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling"

This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".

Openmixup ⭐ 538

CAIRI Supervised, Semi- and Self-Supervised Visual Representation Learning Toolbox and Benchmark

Convmae ⭐ 370

ConvMAE: Masked Convolution Meets Masked Autoencoders

[ICCV 2023] You Only Look at One Partial Sequence

Awesome Mim ⭐ 178

[Survey] Masked Modeling for Self-supervised Representation Learning on Vision and Beyond (https://arxiv.org/abs/2401.00897)

This is a PyTorch implementation of “Context AutoEncoder for Self-Supervised Representation Learning"

Greenmim ⭐ 129

[NeurIPS2022] Official implementation of the paper 'Green Hierarchical Vision Transformer for Masked Image Modeling'.

Official PyTorch implementation of MOOD series: (1) MOODv1: Rethinking Out-of-distributionDetection: Masked Image Modeling Is All You Need. (2) MOODv2: Masked Image Modeling for Out-of-Distribution Detection.

MixMIM: Mixed and Masked Image Modeling for Efficient Visual Representation Learning

PyTorch code for MUST

[CVPR'23] Hard Patches Mining for Masked Image Modeling

Exploring Target Representations for Masked Autoencoders (ICLR2024)

This is a PyTorch implementation of “Context AutoEncoder for Self-Supervised Representation Learning"

[ICML 2023] Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN

Official implementation of Matrix Variational Masked Autoencoder (M-MAE) for paper "Information Flow in Self-Supervised Learning" (https://arxiv.org/abs/2309.17281)

PyTorch implementation for "Training and Inference on Any-Order Autoregressive Models the Right Way", NeurIPS 2022

PyTorch reimplementation of "A simple, efficient and scalable contrastive masked autoencoder for learning visual representations".

[NeurIPS 2023] Masked Image Residual Learning for Scaling Deeper Vision Transformers

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