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Found 30 papers, 12 papers with code
Detect and Locate: Exposing Face Manipulation by Semantic- and Noise-level Telltales
The technological advancements of deep learning have enabled sophisticated face manipulation schemes, raising severe trust issues and security concerns in modern society.
Unsupervised and self-adaptative techniques for cross-domain person re-identification
Person Re-Identification (ReID) across non-overlapping cameras is a challenging task and, for this reason, most works in the prior art rely on supervised feature learning from a labeled dataset to match the same person in different views.
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Unsupervised Domain Adaptation
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Robust Domain Misinformation Detection via Multi-modal Feature Alignment
We also propose a framework that simultaneously considers application scenarios of domain generalization (in which the target domain data is unavailable) and domain adaptation (in which unlabeled target domain data is available).
Ensemble of Multi-View Learning Classifiers for Cross-Domain Iris Presentation Attack Detection
The adoption of large-scale iris recognition systems around the world has brought to light the importance of detecting presentation attack images (textured contact lenses and printouts).
Cross-Domain Iris Presentation Attack Detection
Iris Recognition
+1
Content-Aware Detection of Temporal Metadata Manipulation
Finally, we demonstrate how the proposed method can be employed to estimate a possible time-of-capture in scenarios in which the timestamp is missing from the metadata.
U-Phylogeny: Undirected Provenance Graph Construction in the Wild
Deriving relationships between images and tracing back their history of modifications are at the core of Multimedia Phylogeny solutions, which aim to combat misinformation through doctored visual media.
Leveraging Ensembles and Self-Supervised Learning for Fully-Unsupervised Person Re-Identification and Text Authorship Attribution
We propose a strategy to tackle Person Re-Identification and Text Authorship Attribution by enabling learning from unlabeled data even when samples from different classes are not prominently diverse.
Temporally Sorting Images from Real-World Events
As smartphones become ubiquitous in modern life, every major event — from musical concerts to terrorist attempts — is massively captured by multiple devices and instantly uploaded to the Internet.
Few-shot Learning for Multi-modal Social Media Event Filtering
To the best of our knowledge, this dataset is the first of its kind in event filtering that focuses on protests in multi-modal social media data, with most of the text in Portuguese.
M3FAS: An Accurate and Robust MultiModal Mobile Face Anti-Spoofing System
Face presentation attacks (FPA), also known as face spoofing, have brought increasing concerns to the public through various malicious applications, such as financial fraud and privacy leakage.
Specialized Support Vector Machines for Open-set Recognition
In the open-set scenario, however, a test sample can belong to none of the known classes and the classifier must properly reject it by classifying it as unknown.
Image Provenance Analysis at Scale
Given a large corpus of images and a query image, an interesting further step is to retrieve the set of original images whose content is present in the query image, as well as the detailed sequences of transformations that yield the query image given the original images.
Provenance Filtering for Multimedia Phylogeny
Departing from traditional digital forensics modeling, which seeks to analyze single objects in isolation, multimedia phylogeny analyzes the evolutionary processes that influence digital objects and collections over time.
Spotting the Difference: Context Retrieval and Analysis for Improved Forgery Detection and Localization
As image tampering becomes ever more sophisticated and commonplace, the need for image forensics algorithms that can accurately and quickly detect forgeries grows.
Cross-Domain Face Verification: Matching ID Document and Self-Portrait Photographs
Cross-domain biometrics has been emerging as a new necessity, which poses several additional challenges, including harsh illumination changes, noise, pose variation, among others.
Deep Representations for Iris, Face, and Fingerprint Spoofing Detection
We assume a very limited knowledge about biometric spoofing at the sensor to derive outstanding spoofing detection systems for iris, face, and fingerprint modalities based on two deep learning approaches.
Beyond Pixels: Image Provenance Analysis Leveraging Metadata
Creative works, whether paintings or memes, follow unique journeys that result in their final form.
FaceSpoof Buster: a Presentation Attack Detector Based on Intrinsic Image Properties and Deep Learning
Techniques that rely on trespassing these kind of systems by using a forged biometric sample, such as a printed paper or a recorded video of a genuine access, are known as presentation attacks, but may be also referred in the literature as face spoofing.
Dynamic Spatial Verification for Large-Scale Object-Level Image Retrieval
Images from social media can reflect diverse viewpoints, heated arguments, and expressions of creativity, adding new complexity to retrieval tasks.
An In-Depth Study on Open-Set Camera Model Identification
To deal with this issue, in this paper, we present the first in-depth study on the possibility of solving the camera model identification problem in open-set scenarios.
Learning Transformation-Aware Embeddings for Image Forensics
To establish the efficacy of the proposed approach, comparisons with state-of-the-art handcrafted and deep learning-based descriptors, and image matching approaches are made.
Survey on Reliable Deep Learning-Based Person Re-Identification Models: Are We There Yet?
Intelligent video-surveillance (IVS) is currently an active research field in computer vision and machine learning and provides useful tools for surveillance operators and forensic video investigators.
Benchmarking Scientific Image Forgery Detectors
To mitigate this bottleneck, we present an extendable open-source library that reproduces the most common image forgery operations reported by the research integrity community: duplication, retouching, and cleaning.
Scalable Fact-checking with Human-in-the-Loop
Researchers have been investigating automated solutions for fact-checking in a variety of fronts.
Explainable Fact-checking through Question Answering
Misleading or false information has been creating chaos in some places around the world.
Forensic Analysis of Synthetically Generated Western Blot Images
As a matter of fact, the generation of synthetic content is not restricted to multimedia data like videos, photographs or audio sequences, but covers a significantly vast area that can include biological images as well, such as western blot and microscopic images.
The Age of Synthetic Realities: Challenges and Opportunities
Synthetic realities are digital creations or augmentations that are contextually generated through the use of Artificial Intelligence (AI) methods, leveraging extensive amounts of data to construct new narratives or realities, regardless of the intent to deceive.
Large-scale Fully-Unsupervised Re-Identification
Fully-unsupervised Person and Vehicle Re-Identification have received increasing attention due to their broad applicability in surveillance, forensics, event understanding, and smart cities, without requiring any manual annotation.
Information Forensics and Security: A quarter-century-long journey
Information Forensics and Security (IFS) is an active R&D area whose goal is to ensure that people use devices, data, and intellectual properties for authorized purposes and to facilitate the gathering of solid evidence to hold perpetrators accountable.
Pixel-Inconsistency Modeling for Image Manipulation Localization
Digital image forensics plays a crucial role in image authentication and manipulation localization.
