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Found 6 papers, 4 papers with code
Credible, Unreliable or Leaked?: Evidence Verification for Enhanced Automated Fact-checking
EVVER-Net can be used to filter evidence collected from the Web, thus enhancing the robustness of end-to-end AFC systems.
RED-DOT: Multimodal Fact-checking via Relevant Evidence Detection
Online misinformation is often multimodal in nature, i. e., it is caused by misleading associations between texts and accompanying images.
VERITE: A Robust Benchmark for Multimodal Misinformation Detection Accounting for Unimodal Bias
Multimedia content has become ubiquitous on social media platforms, leading to the rise of multimodal misinformation (MM) and the urgent need for effective strategies to detect and prevent its spread.
Synthetic Misinformers: Generating and Combating Multimodal Misinformation
To address this, we perform a comparative study on existing and new Synthetic Misinformers that involves (1) out-of-context (OOC) image-caption pairs, (2) cross-modal named entity inconsistency (NEI) as well as (3) hybrid approaches and we evaluate them against real-world misinformation; using the COSMOS benchmark.
Design-time Fashion Popularity Forecasting in VR Environments
To this end, we develop a computer vision pipeline fine tuned on fashion imagery in order to extract relevant visual features along with the category and attributes of the garment.
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.
