Design a patches masked autoencoder by CNN
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Updated
Jun 6, 2024 - Python
Design a patches masked autoencoder by CNN
An optimized implementation of masked autoencoders (MAEs)
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
An optimized implementation of spatiotemporal masked autoencoders
Re-implementation of the method proposed in ''DreamDiffusion: Generating High-Quality Images from Brain EEG Signals'' by Y. Bai, X. Wang et al. for Neural Network Course exam Topics
Investigate possibilities for Vision Transformers with multiscale grids
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".
PyTorch implementation of MADE
The code for the paper "Contrastive Masked Autoencoders for Self-Supervised Video Hashing" (AAAI'23)
Project for Computer Vision course @ MSc in Artificial Intelligence, UniVR
Generative modeling and representation learning through reconstruction
HSIMAE: A Unified Masked Autoencoder with large-scale pretraining for Hyperspectral Image Classification
Change detection on satellite images with masked autoencoders.
A Vector Quantized Masked AutoEncoder for speech emotion recognition
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
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