Here are the winners of the Video Browser Showdown from the previous years.
WINNERS 2024
Overall Winner (Best AVS/Experts, AVS/Novices, Visual KIS/Novices, QA/Experts)
VISIONE 5.0: Enhanced User Interface and AI Models for VBS2024.
Giuseppe Amato, Paolo Bolettieri, Fabio Carrara, Fabrizio Falchi, Claudio Gennaro, Nicola Messina, Lucia Vadicamo, and Claudio Vairo – ISTI, CNR, Pisa, Italy
Best Textual KIS/Experts
Optimizing the Interactive Video Retrieval Tool Vibro for the Video Browser Showdown 2024.
Konstantin Schall, Nico Hezel, Kai Barthel, and Klaus Jung – HTW Berlin, University of Applied Sciences – Visual Computing Group, Germany
Best QA/Novices
diveXplore at the Video Browser Showdown 2024.
Klaus Schöffmann and Sahar Nasirihaghighi – Klagenfurt University, Austria
Best Visual KIS/Experts
PraK Tool: An Interactive Search Tool Based on Video Data Services.
Jakub Lokoc, Zuzana Vopálková, Michael Stroh, Raphael Buchmüller, Udo Schlegel – University of Konstanz, Germany and Charles University in Prague, Czech Republic
WINNERS 2023
Best VBS2023 System
Konstantin Schall, Nico Hezel, Kai Uwe Barthel, and Klaus Jung. Vibro: Video Browsing with Semantic and Visual Image Embeddings. HTW Berlin, University of Applied Sciences – Visual Computing Group, Germany
VBS2023 Runner-Up
Giuseppe Amato, Paolo Bolettieri, Fabio Carrara, Fabrizio Falchi, Claudio Gennaro, Nicola Messina, Lucia Vadicamo, and Claudio Vairo. VISIONE at Video Browser Showdown 2023. ISTI-CNR, Pisa, Italy
Best Newcomer
Weixi Song, Jiangshan He, Xinghan Li, Shiwei Feng, and Chao Liang. QIVISE: A Quantum-inspired Interactive Video Search Engine in VBS2023. Wuhan Universtiy, China.
WINNERS 2022
How were winners selected?
From the best scoring teams over all three categories (AVS, KIS visual, KIS textual), we selected the overall winner, the winner of each category (excluding the overall winner), and the best newcomer.
Overall Winner (Best VBS System):
Nico Hezel, Konstantin Schall, Klaus Jung, and Kai Uwe Barthel. Efficient Search and Browsing of Large-Scale Video Collections with Vibro. HTW Berlin, University of Applied Sciences – Visual Computing Group, Germany
Best AVS
Sangmin Lee, Sungjune Park, and Yong Man Ro. IVIST: Interactive Video Search Tool in VBS 2022. KAIST, Daejeon, South Korea
Best KIS visual
Giuseppe Amato, Paolo Bolettieri, Fabio Carrara, Fabrizio Falchi, Claudio Gennaro, Nicola Messina, Lucia Vadicamo, and Claudio Vairo. VISIONE at Video Browser Showdown 2022. ISTI-CNR, Pisa, Italy
Best KIS textual
Jakub Lokoč, František Mejzlík, Tomáš Souček, Patrik Dokoupil, and Ladislav Peška. Video Search with Context-aware Ranker and Relevance Feedback. Charles University, Prague, Czech Republic
Best Newcomer
Tu-Khiem Le, Van-Tu Ninh, Mai-Khiem Tran, Graham Healy, Cathal Gurrin, Minh-Triet Tran. AVSeeker: An Active Video Retrieval Engine VBS2022. Dublin City University, Dublin, Ireland and VNU-HCM, Vietnam
WINNERS 2021
Overall Winners (Best VBS System)
Silvan Heller, Ralph Gasser, Cristina Illi, Maurizio Pasquinelli, Loris Sauter, Florian Spiess. Towards Explainable Interactive Multi-modal Video Retrieval with Vitrivr. University of Basel, Switzerland
Best AVS
Silvan Heller, Ralph Gasser, Cristina Illi, Maurizio Pasquinelli, Loris Sauter, Florian Spiess. Towards Explainable Interactive Multi-modal Video Retrieval with Vitrivr. University of Basel, Switzerland
Best KIS visual
Ladislav Peška, Gregor Kovalčík, Tomáš Souček, Vít Škrhák, Jakub Lokoč. W2VV++ BERT Model at VBS 2021 (VIRET). Charles University, Czech Republic
Best KIST textual
Patrik Veselý, František Mejzlík, Jakub Lokoč. SOMHunter V2 at Video Browser Showdown 2021. Charles University, Czech Republic
WINNERS 2020
Miroslav Kratochvíl, Patrik Veselý, František Mejzlík, and Jakub Lokoč. SOM-Hunter: Video Browsing with Relevance-to-SOM Feedback Loop. Charles University, Prague, Czech Republic
The colleagues from Charles University have also released a lightweight version of SOMHunter, which you can use as a basis to start in VBS. The system is provided with all the necessary metadata for the V3C1 dataset and available here: https://github.com/siret/somhunter
WINNERS 2019
Luca Rossetto, Mahnaz Amiri Parian, Ralph Gasser, Ivan Giangreco, Silvan Heller, Heiko Schuldt. Deep Learning-Based Concept Detection in vitrivr.
University of Basel, Switzerland
WINNERS 2018
Jakub Lokoc, Gregor Kovalcik and Tomas Soucek. Revisiting SIRET Video Retrieval Tool
Charles University in Prague, Czech Republic
WINNERS 2017
Luca Rossetto, Ivan Giangreco, Claudiu Tanase, Heiko Schuldt, Stephane Dupont and Omar Seddati.
Enhanced Retrieval and Browsing in the IMOTION System
WINNERS 2016
Kai Uwe Barthel, Nico Hezel, and Radek Mackowiak (and Florian Barthel),
HTW Berlin, Germany,
Navigating a graph of scenes for exploring large video collections
WINNERS 2015
Adam Blazek, Jakub Lokoc, Filip Matzner, and Tomas Skopal
SIRET Research Group, Charles University in Prague, Czech Republic
Enhanced Signature-based Video Browser
Winners 2014
Jakub Lokoc, Adam Blazek, and Tomas Skopal
SIRET Research Group, Charles University in Prague, Czech Republic
Signature-based Video Browser
They also provide a download of their tool here (implemented for Windows, with .NET):
siret-vbs-2014.zip.
Moreover, you can see an online demo of the system here
Winners 2013
Duy-Dinh Le, Vu Lam, Thanh Duc Ngo, Vinh Quang Tran, Vu Hoang Nguyen, Duc Anh Duong, and Shin’ichi Satoh
National Institute of Informatics / The Graduate University for Advanced Studies, Tokyo, Japan and The University of Information Technology / University of Science, HCM City, Vietnam
NII-UIT-VBS: A Video Browsing Tool for Known Item Search
Winners 2012
Manfred del Fabro and Laszlo Böszörmenyi
Institute of Information Technology (ITEC), Alpen-Adria-Universität Klagenfurt, Austria
AAU Video Browser: Non-Sequential Hierarchical Video Browsing without Content Analysis
