default search action
MediaEval 2021: Online Event
- Steven Hicks, Konstantin Pogorelov, Andreas Lommatzsch, Alba García Seco de Herrera, Pierre-Etienne Martin, Syed Zohaib Hassan, Alastair Porter, Asem Kasem, Stelios Andreadis, Mathias Lux, Marc Gallofré Ocaña, Alex Liu, Martha A. Larson:
Working Notes Proceedings of the MediaEval 2021 Workshop, Online, 13-15 December 2021. CEUR Workshop Proceedings 3181, CEUR-WS.org 2022
FakeNews
- Konstantin Pogorelov, Daniel Thilo Schroeder, Stefan Brenner, Johannes Langguth:
FakeNews: Corona Virus and Conspiracies Multimedia Analysis Task at MediaEval 2021. - Pascal Schröder:
Don't Just Drop Them: Function Words as Features in COVID-19 Related Fake News Classification on Twitter. - Yuta Yanagi, Ryohei Orihara, Yasuyuki Tahara, Yuichi Sei, Akihiko Ohsuga:
Classifying COVID-19 Conspiracy Tweets with Word Embedding and BERT. - Zeshan Khan, Umar Naseer, Muhammad Atif Tahir:
Short Text Classification using TF-IDF Features and Fast Text Learner. - Zeynep Pehlivan:
On The Pursuit of Fake News : Graph Neural Network meets NLP. - Muhieddine Shebaro, Jason Oliver, Tomiwa Olarewaju, Jelena Tesic:
DL-TXST Fake News: Enhancing Tweet Content Classification with Adapted Language Models. - Tuan-An To, Nham-Tan Nguyen, Dinh-Khoi Vo, Nhat-Quynh Le-Pham, Hai-Dang Nguyen, Minh-Triet Tran:
HCMUS MediaEval 2021: Multi-Model Decision Method Applied on Data Augmentation for COVID-19 Conspiracy Theories Classification. - Youri Peskine, Giulio Alfarano, Ismail Harrando, Paolo Papotti, Raphaël Troncy:
Detecting COVID-19-Related Conspiracy Theories in Tweets. - Manfred Moosleitner, Benjamin Murauer:
On the Performance of Different Text Classification Strategies on Conspiracy Classification in Social Media. - Cheikh Brahim El Vaigh, Thomas Girault, Cyrielle Mallart, Duc Hau Nguyen:
Detecting Fake News Conspiracies with Multitask and Prompt-Based Learning. - Olga Papadopoulou, Symeon Papadopoulos:
MeVer team tackling Corona virus and Conspiracies using Ensemble Classification. - Haoming Guo, Tianyi Huang, Huixuan Huang, Mingyue Fan, Gerald Friedland:
Detecting COVID-19 Conspiracy Theories with Transformers and TF-IDF. - Tuan-Luc Huynh, Nhat-Khang Ngô, Phu-Van Nguyen, Thien-Tri Cao, Thanh-Danh Le, Hai-Dang Nguyen, Minh-Triet Tran:
HCMUS at MediaEval2021: Content-Based Misinformation Detection Using ContextualizedWord Embedding from BERT.
NewsImages
- Benjamin Kille, Andreas Lommatzsch, Özlem Özgöbek, Mehdi Elahi, Duc-Tien Dang-Nguyen:
News Images in MediaEval 2021. - Tom Sühr, Ajay Madhavanr, Nasim Jamshidi Avanaki, René Berk, Andreas Lommatzsch:
Image-Text Rematching for News Items using Optimized Embeddings and CNNs in MediaEval NewsImages 2021. - Yuta Fukatsu, Masaki Aono:
Image-Text Re-Matching Using Swin Transformer and DistilBERT. - Mingliang Liang, Martha A. Larson:
Exploring a Pre-trained Model for Re-Matching News Texts and Images. - Lidia Pivovarova, Elaine Zosa:
Visual Topic Modelling for NewsImage Task at MediaEval 2021. - Cláudio Bartolomeu, Rui Nóbrega, David Semedo:
NewsSeek-NOVA at MediaEval 2021: Context-enriched Multimodal Transformers For News Images Re-matching. - Kani Abdul, Kiran Kiran, Max Rudat, Alexandros Vasileiou, Andreas Lommatzsch:
Methods for Text-Image-Rematching using Pair-wise Similarity and Canonical Similarity Analysis. - Thien-Tri Cao, Nhat-Khang Ngô, Thanh Danh Le, Tuan-Luc Huynh, Ngoc Thien Nguyen, Hai-Dang Nguyen, Minh-Triet Tran:
HCMUS at MediaEval 2021: Fine-tuning CLIP for Automatic News-Images Re-Matching. - Yuxiao Zhou, Andres Gonzalez, Parisa Tabassum, Jelena Tesic:
DL-TXST NewsImages: Contextual Feature Enrichment for Image-Text Re-matching. - Martin Ludwig Zehetner, Mohamed Amine Dhiab:
Deep Embedding-based Multimodal Matching for News Articles: Exploring the Effects of Transfer Learning & Data Augmentation.
Medico
- Steven Hicks, Debesh Jha, Vajira Thambawita, Hugo Hammer, Thomas de Lange, Sravanthi Parasa, Michael Riegler, Pål Halvorsen:
Medico Multimedia Task at MediaEval 2021: Transparency in Medical Image Segmentation. - Andrea M. Storås:
Unsupervised Image Segmentation via Self-Supervised Learning Image Classification. - Felicia Ly Jacobsen:
Predictive Uncertainty Masks from Deep Ensembles in Automated Polyp Segmentation. - Quoc-Huy Trinh, Trong-Hieu Nguyen Mau, Minh-Van Nguyen, Van-Son Ho, Tan-Cong Nguyen, Hai-Dang Nguyen, Minh-Triet Tran:
HCMUS-Juniors at Medico Polyp Segmentation Task 2021: Efficient U-Net for Polyps Segmentation. - Zeshan Khan, Mubasher Khan, Mubashir Yasin, Muhammad Hassan, Muhammad Atif Tahir:
Medico 2021: Medical Image Augmentation and Segmentation using Combination of Segmentation Neural Networks. - Saurab Rauniyar, Abhishek Srivastava, Vabesh Kumar Jha, Ritika Kumari Jha, Debesh Jha, Ashish Rauniyar:
Automated Polyp Segmentation in Colonoscopy using MSRFNet. - Sy-Phuc Pham, Hyung-Jeong Yang, Duy-Phuong Dao, Soo-Hyung Kim, Guee-Sang Lee:
A Study on Test-Time Augmentation and Attention Mechanism in DeepLabv3+ for Deep Learning-Based Segmentation. - Nhat-Khang Ngô, Tuan-Luc Huynh, Thanh-Danh Le, Hai-Dang Nguyen, Minh-Triet Tran:
HCMUS at MediaEval2021: Polyps Segmentation using TransFuse with Focal Tversky Loss. - E-Ro Nguyen, Hai-Dang Nguyen, Minh-Triet Tran:
HCMUS at MediaEval2021: PointRend with Attention Fusion Refinement for Polyps Segmentation.
Predicting Media Memorability
- Rukiye Savran Kiziltepe, Mihai Gabriel Constantin, Claire-Hélène Demarty, Graham Healy, Camilo Fosco, Alba García Seco de Herrera, Sebastian Halder, Bogdan Ionescu, Ana Matran-Fernandez, Alan F. Smeaton, Lorin Sweeney:
Overview of The MediaEval 2021 Predicting Media Memorability Task. - Lorin Sweeney, Ana Matran-Fernandez, Sebastian Halder, Alba Garcia Seco de Herrera, Alan F. Smeaton, Graham Healy:
Overview of the EEG Pilot Subtask at MediaEval 2021: Predicting Media Memorability. - Youwei Lu, Xiaoyu Wu:
Cross-modal Interaction for Video Memorability Prediction. - E-Ro Nguyen, Hai-Dang Huynh-Lam, Hai-Dang Nguyen, Minh-Triet Tran:
HCMUS at MediaEval2021: Attention-based Hierarchical Fusion Network for Predicting Media Memorability. - Lorin Sweeney, Graham Healy, Alan F. Smeaton:
Predicting Media Memorability: Comparing Visual, Textual, and Auditory Features. - Ricardo Kleinlein, Cristina Luna Jiménez, Fernando Fernández Martínez:
THAU-UPM at MediaEval 2021: From Video Semantics To Memorability Using Pretrained Transformers. - Alison Reboud, Ismail Harrando, Jorma Laaksonen, Raphaël Troncy:
Exploring Multimodality, Perplexity and Explainability for Memorability Prediction. - Mihai Gabriel Constantin, Bogdan Ionescu:
Using Vision Transformers and Memorable Moments for the Prediction of Video Memorability.
Sports Video
- Pierre-Etienne Martin, Jordan Calandre, Boris Mansencal, Jenny Benois-Pineau, Renaud Péteri, Laurent Mascarilla, Julien Morlier:
Sports Video: Fine-Grained Action Detection and Classification of Table Tennis Strokes from videos for MediaEval 2021. - Pierre-Etienne Martin:
Spatio-Temporal CNN Baseline Method for the Sports Video Task of MediaEval 2021 Benchmark. - Trong-Tung Nguyen, Thanh-Son Nguyen, Gia-Bao Dinh Ho, Hai-Dang Nguyen, Minh-Triet Tran:
HCMUS at MediaEval 2021: Ensembles of Action Recognition Networks with Prior Knowledge for Table Tennis Strokes Classification Task. - Bhuvana J, Mirnalinee T. T, Bharathi B, Jayasooryan S, Lokesh N. N:
YOLOV5 for Stroke Detection and Classification in Table Tennis. - Yijun Qian, Lijun Yu, Wenhe Liu, Alexander Hauptmann:
Learning Unbiased Transformer for Long-Tail Sports Action Classification. - Anam Zahra, Pierre-Etienne Martin:
Two Stream Network for Stroke Detection in Table Tennis.
Visual Sentiment Analysis
- Syed Zohaib Hassan, Kashif Ahmad, Michael Riegler, Steven Hicks, Nicola Conci, Pål Halvorsen, Ala I. Al-Fuqaha:
Visual Sentiment Analysis: A Natural Disaster Use-case Task at MediaEval 2021. - Alexandros Pournaras, Nikolaos Gkalelis, Damianos Galanopoulos, Vasileios Mezaris:
Combining Multiple Deep-learning-based Image Features for Visual Sentiment Analysis. - Khubaib Ahmad, Muhammad Asif Ayub, Kashif Ahmad, Ala I. Al-Fuqaha, Nasir Ahmad:
Deep Models for Visual Sentiment Analysis of Disaster-related Multimedia Content. - Tetsuya Asakawa, Riku Tsuneda, Masaki Aono:
Visual Sentiment Analysis Multiplying Deep learning and Vision Transformers. - Mohsin Ali, Muhammad Hanif, Muhammad Atif Tahir, Muhammad Nouman Durrani, Muhammad Rafi:
Disaster based Visual Sentiment Analysis using Deep Learning. - Bang-Dang Pham, Nhat-Tan Bui, Minh-Khoi Pham, Pham Van Ngoan, Truong-Hai Nguyen, Thang-Long Nguyen-Ho, Hai-Dang Nguyen, Minh-Triet Tran:
HCMUS at MediaEval 2021: Efficient methods of Metadata Embedding and Augmentation for Visual Sentiment Analysis.
Emotions and Themes in Music
- Philip Tovstogan, Dmitry Bogdanov, Alastair Porter:
MediaEval 2021: Emotion and Theme Recognition in Music Using Jamendo. - Maximilian Mayerl, Michael Vötter, Andreas Peintner, Günther Specht, Eva Zangerle:
Recognizing Song Mood and Theme: Clustering-based Ensembles. - Hao Hao Tan:
Semi-Supervised Music Emotion Recognition using Noisy Student Training and Harmonic Pitch Class Profiles. - Vincent Bour:
Frequency Dependent Convolutions for Music Tagging. - Phu-Thinh Pham, Minh-Hieu Huynh, Hai-Dang Nguyen, Minh-Triet Tran:
SELAB-HCMUS at MediaEval 2021: Music Theme and Emotion Classification with Co-teaching Training Strategy.
Insight for Wellbeing
- Asem Kasem, Minh-Son Dao, Effa Nabilla Aziz, Duc-Tien Dang-Nguyen, Cathal Gurrin, Minh-Triet Tran, Nguyen Thanh Binh, Wida Suhaili:
Overview of Insight for Wellbeing Task at MediaEval 2021: Cross-Data Analytics for Transboundary Haze Prediction. - Minh-Anh Ton-Thien, Chuong Thi Nguyen, Quang M. Le, Dat Q. Duong:
Air Quality Estimation Using LSTM and An Approach for Data Processing Techniques. - Ali Akbar, Muhammad Atif Tahir, Muhammad Rafi:
Towards Time Series Forecasting of Cross-Data Analytics for Haze Prediction. - Huu-Vinh Nguyen, Thi Thuy Nga Duong:
Insights for Wellbeing: Predicting PM10 Values Using Stacking Ensemble Model. - Thinh Nguyen, Nazmudeen Mohamed Saleem:
Multimodal Deep Learning for Transboundary Haze Prediction.
WaterMM
- Stelios Andreadis, Ilias Gialampoukidis, Aristeidis Bozas, Anastasia Moumtzidou, Roberto Fiorin, Francesca Lombardo, Anastasios Karakostas, Daniele Norbiato, Stefanos Vrochidis, Michele Ferri, Ioannis Kompatsiaris:
WaterMM: Water Quality in Social Multimedia Task at MediaEval 2021. - Muhammad Asif Ayub, Khubaib Ahmad, Kashif Ahmad, Nasir Ahmad, Ala I. Al-Fuqaha:
NLP Techniques for Water Quality Analysis in Social Media Content. - Muhammad Hanif, Ammar Khawer, Muhammad Atif Tahir, Muhammad Rafi:
Deep Learning Based Framework for Classification of Water Quality in Social Media Data.
Emotional Mario
- Mathias Lux, Michael Riegler, Steven Hicks, Duc-Tien Dang-Nguyen, Kristine Jørgensen, Vajira Thambawita, Pål Halvorsen:
Emotional Mario Task at MediaEval 2021. - Mutaz Alshaer, Kseniia Harshina, Veit Isopp:
Emotional Mario: A Games Analytics Challenge: MediaEval 2021. - Van-Tu Ninh, Tu-Khiem Le, Manh-Duy Nguyen, Sinéad Smyth, Graham Healy, Cathal Gurrin:
A Preliminary Assessment of Game Event Detection in Emotional Mario Task at MediaEval 2021.
Emerging News
- Marc Gallofré Ocaña, Andreas L. Opdahl, Duc-Tien Dang-Nguyen:
Emerging News task: Detecting emerging events from social media and news feeds. - Omar Meriwani:
Mediaeval 2021 Emerging News: Detection of Emerging News from Live News Stream Based on Categorization of News Annotations.
Video Data Privacy
- Alex Liu, Andrew Boka, Asal Baragchizadeh, Chandini Muthukumar, Victoria Huang, Arjun Sarup, Regina Ferrell, Gerald Friedland, Thomas P. Karnowski, Meredith Lee, Alice J. O'Toole:
Overview Paper for Driving Road Safety Forward: Video Data Privacy Task at MediaEval 2021. - Minh-Khoi Pham, Thang-Long Nguyen-Ho, Trong-Thang Pham, Hai-Tuan Ho-Nguyen, Hai-Dang Nguyen, Minh-Triet Tran:
HCMUS at MediaEval 2021: Facial Data De-identification with Adversarial Generation and Perturbation Methods.
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-12-17 20:47 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: