Research Highlights

Out-of-Distribution Learning

Out-of-Distribution Learning

Out-of-Distribution learning is concerned with developing methods where the distribution of the data processed at test time may be different from the distribution of the data used during the training of a model.

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Immersive Analytics

Immersive Analytics

Recent advanecs in augmented, mixed, and virtual reality, coupled with the need to perform analysis and decision-making on large-scale collections of volumetric images stimulate the research in immersive analytics.

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Novelty and Anomaly Detection

Novelty and Anomaly Detection

Detecting the presence of outliers, like novelties or anomalies, with respect to a particular distribution has numerous applications in computer vision and in nearly every area of data science.

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Recent Posts

Aerial Video Analysis

8 minute read

In aerial video moving objects of interest are typically very small, and being able to detect them is key to enable tracking. There are detection methods tha...

Face Modeling and Tracking

2 minute read

Active Appearance Models (AAMs) represent facial images with generative models for both shape and appearance of the face. Despite their success, they enjoy l...

People Detection

3 minute read

People detection and tracking in video are fundamental Computer Vision capabilities that still constitute a research challenge. Important difficulties are du...

Dynamic Texture Editing

5 minute read

The operation that by processing video data allows producing new video data in Computer Graphics is known as Video-Based Rendering (VBR). Developing new VBR ...