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Found 5 papers, 3 papers with code
Bridging Language, Vision and Action: Multimodal VAEs in Robotic Manipulation Tasks
A more lightweight alternative would be the implementation of multimodal Variational Autoencoders (VAEs) which can extract the latent features of the data and integrate them into a joint representation, as has been demonstrated mostly on image-image or image-text data for the state-of-the-art models.
Adaptive Compression of the Latent Space in Variational Autoencoders
Variational Autoencoders (VAEs) are powerful generative models that have been widely used in various fields, including image and text generation.
Imitrob: Imitation Learning Dataset for Training and Evaluating 6D Object Pose Estimators
This paper introduces a dataset for training and evaluating methods for 6D pose estimation of hand-held tools in task demonstrations captured by a standard RGB camera.
Benchmarking Multimodal Variational Autoencoders: CdSprites+ Dataset and Toolkit
Multimodal Variational Autoencoders (VAEs) have been the subject of intense research in the past years as they can integrate multiple modalities into a joint representation and can thus serve as a promising tool for both data classification and generation.
myGym: Modular Toolkit for Visuomotor Robotic Tasks
We introduce a novel virtual robotic toolkit myGym, developed for reinforcement learning (RL), intrinsic motivation and imitation learning tasks trained in a 3D simulator.
