maple-research-lab Goto Github PK
Name: Lab for MAchine Perception and LEarning (MAPLE)
Type: Organization
Blog: http://maple-lab.net/
Name: Lab for MAchine Perception and LEarning (MAPLE)
Type: Organization
Blog: http://maple-lab.net/
AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries
code for "AdPE: Adversarial Positional Embeddings for Pretraining Vision Transformers via MAE+"
Auto-Encoding Transformations (AETv1), CVPR 2019
Autoencoding Variational Transformations (AVT) in pytorch, ICCV 2019
CaCo: Both Positive and Negative Samples are Directly Learnable via Cooperative-adversarial Contrastive Learning
This project is obsolete. New one is at https://github.com/maple-research-lab/CapProNet_tf.
Capsule Projection Networks (CapProNet) in pytorch, NeurIPS 2018
Capsule Projection Networks (CapProNet) in pytorch, NeurIPS 2018
official implemntation for "Contrastive Learning with Stronger Augmentations"
EnAET: Self-Trained Ensemble AutoEncoding Transformations for Semi-Supervised Learning
Generalized Loss-Sensitive GAN in torch, IJCV
Generalized Loss-Sensitive Generative Adversarial Networks (GLS-GAN) in PyTorch with gradient penalty, including both LS-GAN and WGAN as special cases.
GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2020)
Generalized Loss-Sensitive Adversarial Learning implemented in Blocks
Generalized Loss-Sensitive Adversarial Learning in torch
Loss-Sensitive Generative Adversarial Networks (LS-GAN) in torch, IJCV
Loss-Sensitive GAN with gradient penalty in tensorflow
State-Frequency Memory Recurrent Neural Networks, ICML 2017
Transformation GAN for Unsupervised Image Synthesis and Representation Learning, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2020)
Source code for "WCP: Worst-Case Perturbations for Semi-Supervised Deep Learning" in CPVR 2020.
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