Design a patches masked autoencoder by CNN
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Updated
Mar 25, 2024 - Python
Design a patches masked autoencoder by CNN
An optimized implementation of masked autoencoders (MAEs)
A Vector Quantized Masked AutoEncoder for speech emotion recognition
An optimized implementation of spatiotemporal masked autoencoders
PyTorch wrapper for Deep Density Estimation Models
code for "AdPE: Adversarial Positional Embeddings for Pretraining Vision Transformers via MAE+"
Train MAE on Kaggle 2 GPUs (T4x2), Log to Wandb
Investigate possibilities for Vision Transformers with multiscale grids
PyTorch implementation of MADE
The code for the paper "Contrastive Masked Autoencoders for Self-Supervised Video Hashing" (AAAI'23)
TorchGeo: datasets, transforms, and models for geospatial data
Official codebase for "Unveiling the Power of Audio-Visual Early Fusion Transformers with Dense Interactions through Masked Modeling".
Project for Computer Vision course @ MSc in Artificial Intelligence, UniVR
HSIMAE: A Unified Masked Autoencoder with large-scale pretraining for Hyperspectral Image Classification
Generative modeling and representation learning through reconstruction
Change detection on satellite images with masked autoencoders.
Reproducing the MET framework with PyTorch
Codebase for Imperial MSc AI Individual Project - Self-Supervised Learning for Audio Inference
Masked Modeling Duo: Towards a Universal Audio Pre-training Framework
Official implementation of "A simple, efficient and scalable contrastive masked autoencoder for learning visual representations".
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