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Found 5 papers, 4 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.
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.
Where is my forearm? Clustering of body parts from simultaneous tactile and linguistic input using sequential mapping
In species that use language, this process is further structured by this interaction, where a mapping between the sensorimotor concepts and linguistic elements needs to be established.
