masked-autoencoder
There are 50 repositories under masked-autoencoder topic.
keyu-tian/SparK
[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"
MCG-NJU/VideoMAE
[NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
OpenGVLab/InternVideo
Video Foundation Models & Data for Multimodal Understanding
EdisonLeeeee/Awesome-Masked-Autoencoders
A collection of literature after or concurrent with Masked Autoencoder (MAE) (Kaiming He el al.).
Lupin1998/Awesome-MIM
[Survey] Masked Modeling for Self-supervised Representation Learning on Vision and Beyond (https://arxiv.org/abs/2401.00897)
implus/UM-MAE
Official Codes for "Uniform Masking: Enabling MAE Pre-training for Pyramid-based Vision Transformers with Locality"
uncbiag/SimpleClick
SimpleClick: Interactive Image Segmentation with Simple Vision Transformers (ICCV 2023)
xyzforever/BEVT
PyTorch implementation of BEVT (CVPR 2022) https://arxiv.org/abs/2112.01529
implus/mae_segmentation
reproduction of semantic segmentation using masked autoencoder (mae)
ruiwang2021/mvd
[CVPR2023] Masked Video Distillation: Rethinking Masked Feature Modeling for Self-supervised Video Representation Learning (https://arxiv.org/abs/2212.04500)
Haochen-Wang409/HPM
[CVPR'23] Hard Patches Mining for Masked Image Modeling
nttcslab/msm-mae
Masked Spectrogram Modeling using Masked Autoencoders for Learning General-purpose Audio Representations
TonyLianLong/CrossMAE
Official Implementation of the CrossMAE paper: Rethinking Patch Dependence for Masked Autoencoders
rishikksh20/AudioMAE-pytorch
Unofficial PyTorch implementation of Masked Autoencoders that Listen
HKUDS/MAERec
[SIGIR'2023] "MAERec: Graph Masked Autoencoder for Sequential Recommendation"
habla-liaa/encodecmae
Codebase for the paper 'EncodecMAE: Leveraging neural codecs for universal audio representation learning'
nttcslab/m2d
Masked Modeling Duo: Towards a Universal Audio Pre-training Framework
MCG-NJU/VideoMAE-Action-Detection
[NeurIPS 2022 Spotlight] VideoMAE for Action Detection
lyhkevin/MT-Net
Multi-scale Transformer Network for Cross-Modality MR Image Synthesis (IEEE TMI)
shlokk/mae-contrastive
Official implementation of "A simple, efficient and scalable contrastive masked autoencoder for learning visual representations".
liruiw/Dec-SSL
Understanding Self-Supervised Learning in a Decentralized Setting
sunilhoho/VideoMS
Official Pytorch implementation of Efficient Video Representation Learning via Masked Video Modeling with Motion-centric Token Selection.
bayartsogt-ya/albert-mongolian
ALBERT trained on Mongolian text corpus
recursionpharma/maes_microscopy
Official repo for Recursion's accepted spotlight paper at NeurIPS 2023 Generative AI & Biology workshop.
Westlake-AI/A2MIM
[ICML 2023] Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN
jakhac/CSMAE
Cross-Sensor Masked Autoencoder for Content Based Image Retrieval in Remote Sensing
mvrl/BirdSAT
A PyTorch implementation of "BirdSAT: Cross-View Contrastive Masked Autoencoders for Bird Species Classification and Mapping"
JJLi0427/CNN_Masked_Autoencoder
Design a patches masked autoencoder by CNN
stoneMo/DeepAVFusion
Official codebase for "Unveiling the Power of Audio-Visual Early Fusion Transformers with Dense Interactions through Masked Modeling".
waldo-vision/models
Repository for model development and training
samsad35/VQ-MAE-S-code
A Vector Quantized Masked AutoEncoder for speech emotion recognition
yifanzhang-pro/M-MAE
Official implementation of Matrix Variational Masked Autoencoder (M-MAE) for ICML paper "Information Flow in Self-Supervised Learning" (https://arxiv.org/abs/2309.17281)
jonahanton/SSL_audio
Codebase for Imperial MSc AI Individual Project - Self-Supervised Learning for Audio Inference
Video-MAC/VideoMAC
Official code for CVPR2024 “VideoMAC: Video Masked Autoencoders Meet ConvNets”
Ryan21wy/HSIMAE
HSIMAE: A Unified Masked Autoencoder with large-scale pretraining for Hyperspectral Image Classification
YunghuiHsu/ebird_project
Extraction of deep features/representation of birds by deep learning algorithms.