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CLIP4Cir
[ACM TOMM 2023] - Composed Image Retrieval using Contrastive Learning and Task-oriented CLIP-based FeaturesCLIP4CirDemo
[CVPR 2022 - Demo Track] - Effective conditioned and composed image retrieval combining CLIP-based featuresAugmentBrain
In AugmentBrain we investigate the performance of different data augmentation methods for the classification of Motor Imagery (MI) data using a Convolutional Neural Network tailored for EEG named EEGNet.MT-BERT
In MT-BERT we reproduce a neural language understanding model which implements a Multi-Task Deep Neural Network (MT-DNN) for learning representations across multiple NLU tasks.SupeRAuGAN
In SupeRAuGAN we implement a novel data augmentation technique tailored to Generative Adversarial Networks in order to reduce discriminator overfitting and stabilize trainingfacestretch
In facestretch we describe how we exploited the dlib’s facial landmarks in order to measure face deformation and perform an expression recognition task. We implemented multiple approaches, based metric learning, neural networks and geodesic distancesLove Open Source and this site? Check out how you can help us