282 citations · 376 across the 19 of their papers we have counts for
40 papers
Goal-driven Self-Attentive Recurrent Networks for Trajectory Prediction
Luigi Filippo Chiara, Pasquale Coscia, Sourav Das +3
Human trajectory forecasting is a key component of autonomous vehicles, social-aware robots and advanced video-surveillance applications. This challenging task typically requires k…
How many Observations are Enough? Knowledge Distillation for Trajectory Forecasting
Alessio Monti, Angelo Porrello, Simone Calderara +3
Accurate prediction of future human positions is an essential task for modern video-surveillance systems. Current state-of-the-art models usually rely on a "history" of past tracke…
CaMEL: Mean Teacher Learning for Image Captioning
Manuele Barraco, Matteo Stefanini, Marcella Cornia +3
Describing images in natural language is a fundamental step towards the automatic modeling of connections between the visual and textual modalities. In this paper we present CaMEL,…
Multi-Category Mesh Reconstruction From Image Collections
Alessandro Simoni, Stefano Pini, Roberto Vezzani +1
Recently, learning frameworks have shown the capability of inferring the accurate shape, pose, and texture of an object from a single RGB image. However, current methods are traine…
Working Memory Connections for LSTM
Federico Landi, Lorenzo Baraldi, Marcella Cornia +1
Recurrent Neural Networks with Long Short-Term Memory (LSTM) make use of gating mechanisms to mitigate exploding and vanishing gradients when learning long-term dependencies. For t…
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?
Matteo Fabbri, Guillem Braso, Gianluca Maugeri +6
Deep learning-based methods for video pedestrian detection and tracking require large volumes of training data to achieve good performance. However, data acquisition in crowded pub…