SeeForMe on TechCrunch Real-time Wearable Computer Vision System

SeeForMe. Wearable Computer Vision System

Our demo paper “Real-time Wearable Computer Vision System for Improved Museum Experience” at ACM Multimedia 2016 was reported on TechCrunch as worth highlighting!

Read the paper!

SeeForMe is a mobile application which runs on a mobile wearable device and perform real-time object classification and artwork recognition using a wearable device. SeeForMe improves user experience during a museum visit by providing contextual information and performing user profiling.

In the demo paper we propose the use of a compact CNN network that performs object classification and artwork localization and, using the same CNN features, we perform a robust artwork recognition.

Shape based filtering, artwork tracking and temporal filtering further improve recognition accuracy.

Best Poster ACM ICMR 2020

Image Retrieval Using Multi-Scale CNN Feature Pooling

Investigating Nuisance Factors in Face Recognition with DCNN Representation

Best Paper Award

Best Paper Award to our paper on "Face Recognition"

Leonardo Galteri, Marco Bertini, Lorenzo Seidenari, Tiberio Uricchio, Alberto Del Bimbo, Increasing Video Perceptual Quality with GANs and Semantic Coding

ACM MM 2020 Paper

Increasing Video Perceptual Quality

Lamberto Ballan

Sharing Knowledge

for Large Scale Visual Recognition