Search Results for author: Davide Abati

Found 10 papers, 6 papers with code

Delta Distillation for Efficient Video Processing

no code implementations17 Mar 2022 Amirhossein Habibian, Haitam Ben Yahia, Davide Abati, Efstratios Gavves, Fatih Porikli

By extensive experiments on a wide range of architectures, including the most efficient ones, we demonstrate that delta distillation sets a new state of the art in terms of accuracy vs. efficiency trade-off for semantic segmentation and object detection in videos.

Knowledge Distillation object-detection +3

Region-of-Interest Based Neural Video Compression

no code implementations3 Mar 2022 Yura Perugachi-Diaz, Guillaume Sautière, Davide Abati, Yang Yang, Amirhossein Habibian, Taco S Cohen

To the best of our knowledge, our proposals are the first solutions that integrate ROI-based capabilities into neural video compression models.

Quantization Video Compression

Skip-Convolutions for Efficient Video Processing

1 code implementation CVPR 2021 Amirhossein Habibian, Davide Abati, Taco S. Cohen, Babak Ehteshami Bejnordi

We reformulate standard convolution to be efficiently computed on residual frames: each layer is coupled with a binary gate deciding whether a residual is important to the model prediction,~\eg foreground regions, or it can be safely skipped, e. g. background regions.

Model Compression

Dark Experience for General Continual Learning: a Strong, Simple Baseline

2 code implementations NeurIPS 2020 Pietro Buzzega, Matteo Boschini, Angelo Porrello, Davide Abati, Simone Calderara

Continual Learning has inspired a plethora of approaches and evaluation settings; however, the majority of them overlooks the properties of a practical scenario, where the data stream cannot be shaped as a sequence of tasks and offline training is not viable.

Continual Learning Knowledge Distillation

Conditional Channel Gated Networks for Task-Aware Continual Learning

1 code implementation CVPR 2020 Davide Abati, Jakub Tomczak, Tijmen Blankevoort, Simone Calderara, Rita Cucchiara, Babak Ehteshami Bejnordi

Therefore, we additionally introduce a task classifier that predicts the task label of each example, to deal with settings in which a task oracle is not available.

Continual Learning

Classifying Signals on Irregular Domains via Convolutional Cluster Pooling

no code implementations13 Feb 2019 Angelo Porrello, Davide Abati, Simone Calderara, Rita Cucchiara

We present a novel and hierarchical approach for supervised classification of signals spanning over a fixed graph, reflecting shared properties of the dataset.

General Classification

Latent Space Autoregression for Novelty Detection

1 code implementation CVPR 2019 Davide Abati, Angelo Porrello, Simone Calderara, Rita Cucchiara

Novelty detection is commonly referred to as the discrimination of observations that do not conform to a learned model of regularity.

Anomaly Detection Video Anomaly Detection

Learning to Map Vehicles into Bird's Eye View

3 code implementations26 Jun 2017 Andrea Palazzi, Guido Borghi, Davide Abati, Simone Calderara, Rita Cucchiara

Awareness of the road scene is an essential component for both autonomous vehicles and Advances Driver Assistance Systems and is gaining importance both for the academia and car companies.

Autonomous Vehicles

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