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20152022
most citedTransferable Clean-Label Poisoning Attacks on Deep Neural Nets

137 citations · 866 across the 49 of their papers we have counts for

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18 papers · 1 filter

cs.CV2022112 cited

Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models

Manli Shu, Weili Nie, De-An Huang +4

Pre-trained vision-language models (e.g., CLIP) have shown promising zero-shot generalization in many downstream tasks with properly designed text prompts. Instead of relying on ha…

cs.CV20221 cited

A Deep Dive into Dataset Imbalance and Bias in Face Identification

Valeriia Cherepanova, Steven Reich, Samuel Dooley +3

As the deployment of automated face recognition (FR) systems proliferates, bias in these systems is not just an academic question, but a matter of public concern. Media portrayals…

cs.CV20223 cited

Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations

Amin Ghiasi, Hamid Kazemi, Steven Reich +3

Existing techniques for model inversion typically rely on hard-to-tune regularizers, such as total variation or feature regularization, which must be individually calibrated for ea…

cs.CV20212 cited

A Frequency Perspective of Adversarial Robustness

Shishira R Maiya, Max Ehrlich, Vatsal Agarwal +3

Adversarial examples pose a unique challenge for deep learning systems. Despite recent advances in both attacks and defenses, there is still a lack of clarity and consensus in the…

cs.CV20216 cited

Comparing Human and Machine Bias in Face Recognition

Samuel Dooley, Ryan Downing, George Wei +10

Much recent research has uncovered and discussed serious concerns of bias in facial analysis technologies, finding performance disparities between groups of people based on perceiv…

cs.CV202123 cited

The Intrinsic Dimension of Images and Its Impact on Learning

Phillip Pope, Chen Zhu, Ahmed Abdelkader +2

It is widely believed that natural image data exhibits low-dimensional structure despite the high dimensionality of conventional pixel representations. This idea underlies a common…