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Found 3 papers, 1 papers with code
Robustness Evaluation in Hand Pose Estimation Models using Metamorphic Testing
We found that on average more than 80\% of the hands could not be identified by BodyHands, and at least 50\% of hands could not be identified by MediaPipe hands when diagonal motion blur is introduced, while an average of more than 50\% of strongly underexposed hands could not be correctly estimated by NSRM hand.
Metamorphic Testing-based Adversarial Attack to Fool Deepfake Detectors
We performed our evaluations on MesoInception-4 and TwoStreamNet models, which are the state-of-the-art deepfake detection models.
Fairness Evaluation in Deepfake Detection Models using Metamorphic Testing
Metamorphic relations are derived based on the notion that realistic perturbations of the input images, such as makeup, involving eyeliners, eyeshadows, blushes, and lipsticks (which are common cosmetic appearance) applied to male and female images, should not alter the output of the model by a huge margin.
