MediaEval 2020
Multimedia Benchmark Workshop 2020

Table of Contents

Medico Multimedia Task

Overview paper:

• Medico Multimedia Task at MediaEval 2020: Automatic Polyp Segmentation
  Debesh Jha, Steven Hicks, Krister Emanuelsen, Håvard Johansen, Dag Johansen, Thomas de Lange, Michael A. Riegler, Pål Halvorsen

Working notes papers:

• Bigger Networks are not Always Better: Deep Convolutional Neural Networks for Automated Polyp Segmentation
  Adrian Krenzer, Frank Puppe

• Pyramid-Focus-Augmentation: Medical Image Segmentation with Step-Wise Focus
  Vajira Thambawita, Steven Hicks, Pål Halvorsen, Michael A. Riegler

• Generative Adversarial Networks for Automatic Polyp Segmentation
  Awadelrahman Mohamedelsadig Ali Ahmed

• Transfer of Knowledge: Fine-tuning for Polyp Segmentation with Attention
  Rabindra Khadka

• HCMUS-Juniors 2020 at Medico Task in MediaEval 2020: Refined Deep Neural Network and U-Net for Polyps Segmentation
  Quoc-Huy Trinh, Minh-Van Nguyen, Thiet-Gia Huynh, Minh-Triet Tran

• A Temporal-Spatial Attention Model for Medical Image Detection
  Hwang Maxwell, Wu Cai, Hwang Kao-Shing, Xu Yong Si, Wu Chien-Hsing

• Deep Conditional Adversarial Learning for Polyp Segmentation
  Debapriya Banik , Debotosh Bhattacharjee

• Automatic Polyp Segmentation Using Channel-Spatial Attention with Deep Supervision
  Sahadev Poudel, Sang-Woong Lee

• Automatic Polyp Segmentation Using Fully Convolutional Neural Network
  Nikhil Kumar Tomar

• Automatic Polyp Segmentation via Parallel Reverse Attention Network
  Ge-Peng Ji, Deng-Ping Fan, Tao Zhou, Geng Chen, Huazhu Fu, Ling Shao

• Real-Time Polyp Segmentation Using U-Net with IoU Loss
  George Batchkala, Sharib Ali

• Depth-Wise Separable Atrous Convolution for Polyps Segmentation in Gastro-Intestinal Tract
  Syed Muhammad Faraz Ali, Muhammad Taha Khan, Syed Unaiz Haider, Talha Ahmed, Zeshan Khan, Muhammad Atif Tahir

• HCMUS at Medico Automatic Polyp Segmentation Task 2020: PraNet and ResUnet++ for Polyps Segmentation
  Tien-Phat Nguyen, Tan-Cong Nguyen, Gia-Han Diep, Minh-Quan Le, Hoang-Phuc Nguyen-Dinh, Hai-Dang Nguyen, Minh-Triet Tran

• Ensemble U-Net Model for Efficient Polyp Segmentation
  Shruti Shrestha, Bishesh Khanal, Sharib Ali

• Efficient Supervision Net: Polyp Segmentation Using EfficientNet and Attention Unit
  Sabari Nathan, Suganya Ramamoorthy

• KD-ResUNet++: Automatic Polyp Segmentation via Self-Knowledge Distillation
  Jaeyong Kang, Jeonghwan Gwak

• Automatic Polyp Segmentation Using U-Net-ResNet50
  Saruar Alam, Nikhil Kumar Tomar, Aarati Thakur, Debesh Jha, Ashish Rauniyar

FakeNews

Overview paper:

• FakeNews: Corona Virus and 5G Conspiracy Task at MediaEval 2020
  Konstantin Pogorelov, Daniel Thilo Schroeder, Luk Burchard, Johannes Moe, Stefan Brenner, Petra Filkukova, Johannes Langguth

Working notes papers:

• Detecting Conspiracy Tweets Using Support Vector Machines
  Manfred Moosleitner, Benjamin Murauer, Günther Specht

• MediaEval 2020: An Ensemble-based Multimodal Approach for Coronavirus and 5G Conspiracy Tweet Detection
  Chahat Raj, Mihir Mehta

• Fake News Classification with BERT
  Andrey Malakhov, Alessandro Patruno, Stefano Bocconi

• FakeNews Detection Using Pre-trained Language Models and Graph Convolutional Networks
  Manh Duc Tuan Nguyen, Minh Quang Nhat Pham

• Fake News Detection in Social Media Using Graph Neural Networks and NLP Techniques: A COVID-19 Use-Case
  Abdullah Hamid, Nasrullah Sheikh, Naina Said, Kashif Ahmad, Asma Gul, Laiq Hasan, Ala Al-Fuqaha

• TIB's Visual Analytics Group at MediaEval '20: Detecting Fake News on Corona Virus and 5G Conspiracy
  Gullal Singh Cheema, Sherzod Hakimov, Ralph Ewerth

• You Said It? How Mis- and Disinformation Tweets Surrounding the Corona-5G-Conspiracy Communicate Through Implying
  Lynn de Rijk

• Using a Word Analysis Method and GNNs to Classify Misinformation Related to 5G-Conspiracy and the COVID-19 Pandemic
  Ferdinand Schaal, Jesper Phillips

• Detecting Fake News in Tweets from Text and Propagation Graph: IRISA's Paritcipation to the FakeNews Task at MediaEval 2020
  Vincent Claveau

• Evaluating Standard Classifiers for Detecting COVID-19 Related Misinformation
  Daniel Thilo Schroeder, Konstantin Pogorelov, Johannes Langguth

• Enriching Content Analysis of Tweets Using Community Discovery Graph Analysis
  Andrew Magill, Lia Nogueira de Moura, Maria Tomasso, Mirna Elizondo, Jelena Tesic

• Detecting Conspiracy Theories from Tweets: Textual and Structural Approaches
  Haoming Guo, Adam Ash, David Chung, Gerald Friedland

• On the pursuit of Fake News : From Graph Convolutional Networks to Time Series
  Zeynep Pehlivan

• MeVer Team Tackling Corona Virus and 5G Conspiracy Using Ensemble Classification Based on BERT
  Olga Papadopoulou, Giorgos Kordopatis-Zilos, Symeon Papadopoulos

Predicting Media Memorability

Overview paper:

• Overview of MediaEval 2020 Predicting Media Memorability Task: What Makes a Video Memorable?
  Alba García Seco De Herrera, Rukiye Savran Kiziltepe, Jon Chamberlain, Mihai Gabriel Constantin, Claire-Hélène Demarty, Faiyaz Doctor, Bogdan Ionescu, Alan F. Smeaton

Working notes papers:

• Media Memorability Prediction Based on Machine Learning
  Dazhan Xu, Xiaoyu Wu, Guoquan Sun

• Investigating Memorability of Dynamic Media
  Phuc H. Le-Khac, Ayush K. Rai, Graham Healy, Alan F. Smeaton, Noel E. O’connor

• Leveraging Audio Gestalt to Predict Media Memorability
  Lorin Sweeney, Graham Healy, Alan F. Smeaton

• Essex-NLIP at MediaEval Predicting Media Memorability 2020 Task
  Janadhip Jacutprakart, Rukiye Savran Kiziltepe, John Q. Gan, Giorgos Papanastasiou, Alba G. Seco de Herrera

• Multi-Modal Ensemble Models for Predicting Video Memorability
  Tony Zhao, Irving Fang, Jeffrey Kim, Gerald Friedland

• Predicting Media Memorability with Audio, Video, and Text representations
  Alison Reboud, Ismail Harrando, Jorma Laaksonen, Raphaël Troncy

• Predicting Media Memorability from a Multimodal Late Fusion of Self-Attention and LSTM Models
  Ricardo Kleinlein, Cristina Luna-Jiménez, Zoraida Callejas, Fernando Fernández-Martínez

Emotions and Themes in Music

Overview paper:

• MediaEval 2020: Emotion and Theme Recognition in Music Using Jamendo
  Dmitry Bogdanov, Alastair Porter, Philip Tovstogan, Minz Won

Working notes papers:

• Recognizing Song Mood and Theme: Leveraging Ensembles of Tag Groups
  Michael Vötter, Maximilian Mayerl, Günther Specht, Eva Zangerle

• Emotion and Theme Recognition in Music Using Attention-Based Methods
  Srividya Tirunellai Rajamani, Kumar Rajamani, Björn Schuller

• HCMUS at MediaEval 2020: Emotion Classification Using Wavenet Feature with SpecAugment and EfficientNet
  Tri-Nhan Do, Minh-Tri Nguyen, Hai-Dang Nguyen, Minh-Triet Tran, Xuan-Nam Cao

• Emotion and Themes Recognition in Music with Convolutional and Recurrent Attention-Blocks
  Maurice Gerczuk, Shahin Amiriparian, Sandra Ottl, Srividya Tirunellai Rajamani, Björn Schuller

• MediaEval 2020 Emotion and Theme Recognition in Music Task: Loss Function Approaches for Multi-label Music Tagging
  Dillon Knox, Timothy Greer, Benjamin Ma, Emily Kuo, Krishna Somandepalli, Shrikanth Narayanan

• Recognizing Music Mood and Theme Using Convolutional Neural Networks and Attention
  Alish Dipani, Gaurav Iyer, Veeky Baths

Sports Video Classification

Overview paper:

• Sports Video Classification: Classification of Strokes in Table Tennis for MediaEval 2020
  Pierre-Etienne Martin, Jenny Benois-Pineau, Boris Mansencal, Renaud Péteri, Laurent Mascarilla, Jordan Calandre, Julien Morlier

Working notes papers:

• Leveraging Human Pose Estimation Model for Stroke Classification in Table Tennis
  Soichiro Sato, Masaki Aono

• Four-Stream Network and Dynamic Images for Sports Video Classification: Classification of Strokes in Table Tennis
  Jordan Calandre, Renaud Péteri, Laurent Mascarilla

• HCMUS at MediaEval 2020: Ensembles of Temporal Deep Neural Networks for Table Tennis Strokes Classification Task
  Hai Nguyen-Truong, San Cao, N. A. Khoa Nguyen, Bang-Dang Pham, Hieu Dao, Minh-Quan Le, Hoang-Phuc Nguyen-Dinh, Hai-Dang Nguyen, Minh-Triet Tran

• Spatio-Temporal Based Table Tennis Hit Assessment Using LSTM Algorithm
  Kadir Aktas, Mehmet Demirel, Marilin Moor, Johanna Olesk, Gholamreza Anbarjafari

• Classification of Strokes in Table Tennis with a Three Stream Spatio-Temporal CNN for MediaEval 2020
  Pierre-Etienne Martin, Jenny Benois-Pineau, Boris Mansencal, Renaud Péteri, Julien Morlier

Flood-Related Multimedia

Overview paper:

• The Flood-Related Multimedia Task at MediaEval 2020
  Stelios Andreadis, Ilias Gialampoukidis, Anastasios Karakostas, Stefanos Vrochidis, Ioannis Kompatsiaris, Roberto Fiorin, Daniele Norbiato, Michele Ferri

Working notes papers:

• Flood Detection in Twitter Using a Novel Learning Method for Neural Networks
  Rabiul Islam Jony, Alan Woodley

• A Tweet Text Binary Artificial Neural Network Classifier
  Theodore Nikoletopoulos, Claudia Wolff

• Floods Detection in Twitter Text and Images
  Naina Said, Kashif Ahmad, Asma Gul, Nasir Ahmad, Ala Al-Fuqaha

• Flood Detection via Twitter Streams Using Textual and Visual Features
  Firoj Alam, Zohaib Hassan, Kashif Ahmad, Asma Gul, Michael Reiglar, Nicola Conci, Ala Al-Fuqaha

• Ensemble Based Method for the Classification of Flooding Event Using Social Media Data
  Muhammad Hanif, Huzaifa Joozer, Muhammad Atif Tahir, Muhammad Rafi

Insight for Wellbeing

Overview paper:

• Overview of MediaEval 2020 Insights for Wellbeing: Multimodal Personal Health Lifelog Data Analysis
  Peijiang Zhao, Minh-Son Dao, Thanh Nguyen, Thanh-Binh Nguyen, Duc-Tien Dang-Nguyen, Cathal Gurrin

Working notes papers:

• A2QI: An Approach for Air Pollution Estimation in MediaEval 2020
  Dat Q. Duong, Quang M. Le, Dat T. Nguyen

• Personal Air Quality Index Prediction Using Inverse Distance Weighting Method
  Trung-Quan Nguyen, Dang-Hieu Nguyen, Loc Tai Tan Nguyen

• Use Visual Features From Surrounding Scenes to Improve Personal Air Quality Data Prediction Performance
  Trung-Quan Nguyen, Dang-Hieu Nguyen, Loc Tai Tan Nguyen

• Insights for Wellbeing: Predicting Personal Air Quality Index Using Regression Approach
  Amel Ksibi, Amina Salhi, Ala Alluhaidan, Sahar A. El-Rahman

Pixel Privacy

Overview paper:

• Pixel Privacy: Quality Camouflage for Social Images
  Zhuoran Liu, Zhengyu Zhao, Martha Larson, Laurent Amsaleg

Working notes papers:

• Fooling Blind Image Quality Assessment by Optimizing a Human-Understandable Color Filter
  Zhengyu Zhao

• MediaEval 2020: Maintaining Human-Imperceptibility of Image Adversarial Attack by Using Human-Aware Sensitivity Map
  Zhiqi Shen, Muhammad Habibi, Shaojing Fan, Mohan Kankanhalli

• HCMUS at Pixel Privacy 2020: Quality Camouflage with Back Propagation and Image Enhancement
  Minh-Khoi Pham, Hai-Tuan Ho-Nguyen, Trong-Thang Pham, Hung Vinh Tran, Hai-Dang Nguyen, Minh-Triet Tran

• Fooling an Automatic Image Quality Estimator
  Benoit Bonnet, Teddy Furon, Patrick Bas

No-Audio Multimodal Speech Detection Task

Overview paper:

• No-Audio Multimodal Speech Detection Task at MediaEval 2020
  Laura Cabrera-Quiros, Jose Vargas-Quirós, Hayley Hung

Working notes papers:

• Multimodal Fusion of Body Movement Signals for No-audio Speech Detection
  Xinsheng Wang, Jihua Zhu, Odette Scharenborg

NewsImages

Overview paper:

• News Images in MediaEval 2020
  Benjamin Kille, Andreas Lommatzsch, Özlem Özgöbek

Working notes papers:

• HCMUS at MediaEval 2020: Image-Text Fusion for Automatic News-Images Re-Matching
  Thuc Nguyen-Quang, Tuan-Duy Nguyen, Thang-Long Nguyen-Ho, Anh-Kiet Duong, Xuan-Nhat Hoang, Vinh-Thuyen Nguyen-Truong, Hai-Dang Nguyen, Minh-Triet Tran