QuAD aggregates quality-weighted detection scores from near-duplicates of an image to raise balanced accuracy by about 8% over simple averaging on state-of-the-art detectors.
Bridging the Gap Between Ideal and Real-world Evaluation: Benchmarking AI-Generated Image Detection in Challeng- ing Scenarios
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Quality-Aware Calibration for AI-Generated Image Detection in the Wild
QuAD aggregates quality-weighted detection scores from near-duplicates of an image to raise balanced accuracy by about 8% over simple averaging on state-of-the-art detectors.