Search Results for author:
Found 29 papers, 14 papers with code
User Identity Linkage in Social Media Using Linguistic and Social Interaction Features
Social media users often hold several accounts in their effort to multiply the spread of their thoughts, ideas, and viewpoints.
AI and Non AI Assessments for Dementia
Thus, this paper, which can be readable by both clinicians and AI engineers, fills the gap in the literature in explaining the existing solutions for the recognition of dementia to clinicians, as well as the techniques used and the most widespread dementia datasets to AI engineers.
Improving Synthetically Generated Image Detection in Cross-Concept Settings
New advancements for the detection of synthetic images are critical for fighting disinformation, as the capabilities of generative AI models continuously evolve and can lead to hyper-realistic synthetic imagery at unprecedented scale and speed.
Investigation of ensemble methods for the detection of deepfake face manipulations
The recent wave of AI research has enabled a new brand of synthetic media, called deepfakes.
Self-Supervised Video Similarity Learning
We introduce S$^2$VS, a video similarity learning approach with self-supervision.
Ranked #1 on
Video Retrieval
on FIVR-200K
Multilingual Alzheimer's Dementia Recognition through Spontaneous Speech: a Signal Processing Grand Challenge
This Signal Processing Grand Challenge (SPGC) targets a difficult automatic prediction problem of societal and medical relevance, namely, the detection of Alzheimer's Dementia (AD).
A Multi-Stream Fusion Network for Image Splicing Localization
In this paper, we address the problem of image splicing localization with a multi-stream network architecture that processes the raw RGB image in parallel with other handcrafted forensic signals.
VICTOR: Visual Incompatibility Detection with Transformers and Fashion-specific contrastive pre-training
For fashion outfits to be considered aesthetically pleasing, the garments that constitute them need to be compatible in terms of visual aspects, such as style, category and color.
InDistill: Information flow-preserving knowledge distillation for model compression
In this paper we introduce InDistill, a model compression approach that combines knowledge distillation and channel pruning in a unified framework for the transfer of the critical information flow paths from a heavyweight teacher to a lightweight student.
The MeVer DeepFake Detection Service: Lessons Learnt from Developing and Deploying in the Wild
Enabled by recent improvements in generation methodologies, DeepFakes have become mainstream due to their increasingly better visual quality, the increase in easy-to-use generation tools and the rapid dissemination through social media.
Multimodal Quasi-AutoRegression: Forecasting the visual popularity of new fashion products
We employ the product's target attributes time series as a proxy of temporal popularity patterns, mitigating the lack of historical data, while exogenous time series help capture trends among interrelated attributes.
Ranked #1 on
Popularity Forecasting
on SHIFT15M
p2pGNN: A Decentralized Graph Neural Network for Node Classification in Peer-to-Peer Networks
In this work, we aim to classify nodes of unstructured peer-to-peer networks with communication uncertainty, such as users of decentralized social networks.
pygrank: A Python Package for Graph Node Ranking
We introduce pygrank, an open source Python package to define, run and evaluate node ranking algorithms.
A Survey on Bias in Visual Datasets
Hence, this work aims to: i) describe the biases that might manifest in visual datasets; ii) review the literature on methods for bias discovery and quantification in visual datasets; iii) discuss existing attempts to collect bias-aware visual datasets.
DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval
In this work, we propose a Knowledge Distillation framework, called Distill-and-Select (DnS), that starting from a well-performing fine-grained Teacher Network learns: a) Student Networks at different retrieval performance and computational efficiency trade-offs and b) a Selector Network that at test time rapidly directs samples to the appropriate student to maintain both high retrieval performance and high computational efficiency.
Ranked #2 on
Video Retrieval
on FIVR-200K
Leveraging EfficientNet and Contrastive Learning for Accurate Global-scale Location Estimation
In this paper, we address the problem of global-scale image geolocation, proposing a mixed classification-retrieval scheme.
Operation-wise Attention Network for Tampering Localization Fusion
In this work, we present a deep learning-based approach for image tampering localization fusion.
Audio-based Near-Duplicate Video Retrieval with Audio Similarity Learning
For the robust similarity calculation between two videos, we first extract representative audio-based video descriptors by leveraging transfer learning based on a Convolutional Neural Network (CNN) trained on a large scale dataset of audio events, and then we calculate the similarity matrix derived from the pairwise similarity of these descriptors.
LAVARNET: Neural Network Modeling of Causal Variable Relationships for Multivariate Time Series Forecasting
Multivariate time series forecasting is of great importance to many scientific disciplines and industrial sectors.
Investigating the Impact of Pre-processing and Prediction Aggregation on the DeepFake Detection Task
In this paper, we propose a pre-processing step to improve the training data quality and examine its effect on the performance of DeepFake detection.
MuSe 2020 -- The First International Multimodal Sentiment Analysis in Real-life Media Challenge and Workshop
Multimodal Sentiment Analysis in Real-life Media (MuSe) 2020 is a Challenge-based Workshop focusing on the tasks of sentiment recognition, as well as emotion-target engagement and trustworthiness detection by means of more comprehensively integrating the audio-visual and language modalities.
ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning
Subsequently, the similarity matrix between all video frames is fed to a four-layer CNN, and then summarized using Chamfer Similarity (CS) into a video-to-video similarity score -- this avoids feature aggregation before the similarity calculation between videos and captures the temporal similarity patterns between matching frame sequences.
Ranked #5 on
Video Retrieval
on FIVR-200K
FIVR: Fine-grained Incident Video Retrieval
To create the dataset, we devise a process for the collection of YouTube videos based on major news events from recent years crawled from Wikipedia and deploy a retrieval pipeline for the automatic selection of query videos based on their estimated suitability as benchmarks.
A Two-Level Classification Approach for Detecting Clickbait Posts using Text-Based Features
The detector is based almost exclusively on text-based features taken from previous work on clickbait detection, our own work on fake post detection, and features we designed specifically for the challenge.
The Dem@Care Experiments and Datasets: a Technical Report
The objective of Dem@Care is the development of a complete system providing personal health services to people with dementia, as well as medical professionals and caregivers, by using a multitude of sensors, for context-aware, multi-parametric monitoring of lifestyle, ambient environment, and health parameters.
Comparative evaluation of state-of-the-art algorithms for SSVEP-based BCIs
Brain-computer interfaces (BCIs) have been gaining momentum in making human-computer interaction more natural, especially for people with neuro-muscular disabilities.
Monitoring Term Drift Based on Semantic Consistency in an Evolving Vector Field
Based on the Aristotelian concept of potentiality vs. actuality allowing for the study of energy and dynamics in language, we propose a field approach to lexical analysis.
