activity
20162026
most citedWorking Memory Connections for LSTM

282 citations · 326 across the 38 of their papers we have counts for

collaborators
Showing 2019Show all

6 papers · 1 filter

cs.CV2019

Meshed-Memory Transformer for Image Captioning

Marcella Cornia, Matteo Stefanini, Lorenzo Baraldi +1

Transformer-based architectures represent the state of the art in sequence modeling tasks like machine translation and language understanding. Their applicability to multi-modal co…

cs.CV2019

Video action detection by learning graph-based spatio-temporal interactions

Matteo Tomei, Lorenzo Baraldi, Simone Calderara +2

Action Detection is a complex task that aims to detect and classify human actions in video clips. Typically, it has been addressed by processing fine-grained features extracted fro…

cs.CV2019

SMArT: Training Shallow Memory-aware Transformers for Robotic Explainability

Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara

The ability to generate natural language explanations conditioned on the visual perception is a crucial step towards autonomous agents which can explain themselves and communicate…

cs.CV2019

Embodied Vision-and-Language Navigation with Dynamic Convolutional Filters

Federico Landi, Lorenzo Baraldi, Massimiliano Corsini +1

In Vision-and-Language Navigation (VLN), an embodied agent needs to reach a target destination with the only guidance of a natural language instruction. To explore the environment…

cs.LG20191 cited

A Deep Learning based approach to VM behavior identification in cloud systems

Matteo Stefanini, Riccardo Lancellotti, Lorenzo Baraldi +1

Cloud computing data centers are growing in size and complexity to the point where monitoring and management of the infrastructure become a challenge due to scalability issues. A p…

cs.CV201928 cited

M-VAD Names: a Dataset for Video Captioning with Naming

Stefano Pini, Marcella Cornia, Federico Bolelli +2

Current movie captioning architectures are not capable of mentioning characters with their proper name, replacing them with a generic "someone" tag. The lack of movie description d…