European Researchers’ Night: “Science is wonder-ful!”

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By , September 29, 2017

This 26 and 27 September 2017, I was involved in the kickoff event for European Researchers’ Night in Brussels #MSCAnight. With thousands of visitors, most of which were children, it was a smashing success! I have presented my research on machine learning and visual perception, and talked about visual illusions and teaching computers to see.

More about the event: https://goo.gl/QNkxgY, more about my work and some nice pictures.

Aloha CVPR’17: I will be giving two talks on July 26

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By , July 22, 2017

CVPR is growing exponentially. This year in the beautiful Honolulu there are approx. 5K attendees. First, I will present our paper on “Localization of JPEG double compression through multi-domain convolutional neural networks” (Amerini, Uricchio, Ballan, Caldelli) at the CVPR’17 Workshop on Media Forensics. Then, I will give a keynote talk on “Exploiting noisy web data for large-scale visual recognition” at the CVPR’17 Workshop on Visual Understanding by Learning from Web Data [slides available online].

New papers on image tagging and webly-supervised action recognition

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By , July 21, 2017

Our paper “Automatic Image Annotation via Label Transfer in the Semantic Space”, by T. Uricchio, myself, L. Seidenari and A. Del Bimbo, has been accepted for publication in Pattern Recognition and is now available online. It is an extended version of our KCCA-based tag propagation model presented in our ICMR’14 paper, containing more experiments and a novel tag denoising procedure.

A few days later, our paper “Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition” has been also accepted for publication in Computer Vision and Image Understanding (CVIU) and is now available online. Here we present a (fully) webly-supervised model for action recognition in videos. This is a joint work with F. Tombari and C. Rupprecht from TUM (Germany).

I will be joining the University of Padova!

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By , February 3, 2017

Univ. of Padova, Palazzo BoHappy to share that I will join the Math & CS Department of the University of Padova as an Assistant Professor (tenure track) of Computer Science, starting in Fall 2017.

The University of Padova is one of Europe’s oldest and most prestigious seats of learning. The University of Padova is ranked first among Italian universities according to most international rankings (ARWU, US-News) and research evaluation agencies (ANVUR) [UniPD at a glance].

Universa Universis Patavina Libertas.

Invited Talk: Sharing Knowledge for Large Scale Visual Recognition

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By , November 18, 2016

In the last months I gave several times this talk about my recent work on knowledge transfer for large-scale visual recognition problems (e.g. Aquifi Inc – Palo Alto, Google ResearchUC Santa Cruz, MICCU. of Parma, U. of Catania, U. of Padova, “Ca’ Foscari” U. Venice). The key idea of this work is to transfer prior contextual knowledge to novel scenes where it is hard to collect large-scale training data [slides available online].

Marie Curie Fellow of the week

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By , November 11, 2016

I have been selected Marie Curie Fellow of the week! Marie Sklodowska-Curie Actions (MSCA) Individual Fellowships are highly prestigious and competitive and are meant to support the best, most promising European researchers.

More info on this Facebook post.

CVIU Special Issue on Computer Vision and the Web

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By , September 14, 2016

cviuI am co-organizing a special issue for the Computer Vision and Image Understanding journal on “Computer Vision and the Web”, together with Shih-Fu Chang (Columbia University), Gang Hua (Microsoft Research Asia), Thomas Mensink (Univ. of Amsterdam), Greg Mori (Simon Fraser Univ.) and Rahul Sukthankar (Google Research). You can see all the details on the call for papers.

ECCV’16 Paper on Knowledge Transfer for Trajectory Prediction

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By , July 28, 2016

Our paper “Knowledge Transfer for Scene-specific Motion Prediction”, by L. Ballan, F. Castaldo, A. Alahi, F. Palmieri and S. Savarese, has been accepted to ECCV 2016. A pre-print is available on arXiv.

When given a single frame of the video, humans can not only interpret the content of the scene, but also they are able to forecast the near future. This ability is mostly driven by their rich prior knowledge about the visual world, both in terms of (i) the dynamics of moving agents, as well as (ii) the semantic of the scene. We exploit the interplay between these two key elements to predict scene-specific motion patterns.

SAILORS 2016: AI will change the world. Who will change AI?

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By , July 22, 2016

2016_sailors_projects_lambertoIn the past two weeks I have been involved as computer vision project mentor in the Stanford Artificial Intelligence Laboratory’s OutReach Summer program (SAILORS). SAILORS is a summer camp for high school girls and it is intended to increase diversity in the field of AI. SAILORS aims to teach technically rigorous AI concepts in the context of societal impact.

Check out SAILORS blog to know more about the program. SAILORS was also recently featured in Wired.

CVPR’16 Tutorial on Image Tag Assignment, Refinement and Retrieval

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By , June 27, 2016

Cees Snoek and Lamberto Ballan - CVPR 2016We gave a tutorial on “Image Tag Assignment, Refinement and Retrieval” at CVPR 2016, based on our survey. The focus is on challenges and solutions for content-based image retrieval in the context of online image sharing. We present a unified review on three problems: tag assignment, refinement, and tag-based image retrieval.

The slides are available on this page.

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