ATransCribe is a speech-to-text service. It uses Whisper model for transcription. Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech ... read more of atranscribe

a service for automated clustering of Sentinel-2 pixels which allows its users to focus on Earth surface changes rather than on remote sensing problems, and hence to develop their own downstream applications. read more of QuantEO

Descriptions of the implementation of the Vessel Traffic Flow Forecasting (VTFF) model that forecasts the vessel traffic flow within a given region. read more of Vessel Traffic Flow Forecasting (VTFF) using Machine Learning Methods

An improved version of the core parts of the code that implements the Vessel Location Forecasting (VLF) and Vessel Route Forecasting (VRF) methods. read more of An Efficient LSTM Neural Network-Based Framework for Vessel Location Forecasting

Novel framework for Playable Video Generation that is trained in a self-supervised manner on a large dataset of unlabelled videos. We employ an encoder-decoder architecture where the predicted action labels act as bottleneck. The network is constrained to... read more of Playable Video Generation

A holistic learning framework for Novel Class Discovery (NCD), which adopts contrastive learning to learn discriminate features with both the labeled and unlabeled data. The Neighborhood Contrastive Learning (NCL) framework effectively leverages the local... read more of Neighborhood Contrastive Learning for Novel Class Discovery

PyTorch implementation of Intrinsic-Extrinsic Preserved Generative Adversarial Network (IEP-GAN) for both intrinsic (i.e., shape) and extrinsic (i.e., pose) information preservation. Extrinsically, a co-occurrence discriminator is used to capture the stru... read more of IEP-GAN: Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer

A tool to allow Visual Transformers (VTs) to learn spatial relations within an image making the VT training much more robust when training data is scarce. The tool can be used jointly with the standard (supervised) training and it does not depend on speci... read more of Efficient Training of Visual Transformers with Small Datasets

Python implementation of novel Cycle In Cycle Generative Adversarial Network (C2GAN) for the task of keypoint-guided image generation. The C2GAN is a cross-modal framework exploring a joint exploitation of the keypoint and the image data in an interactive... read more of Cycle-In-Cycle GANs

A novel unsupervised domain adaptation approach for action recognition from videos, inspired by recent literature on contrastive learning. It comprises a novel two-headed deep architecture that simultaneously adopts cross-entropy and contrastive losses fr... read more of CO2A - Contrastive Conditional domain Alignment