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20172024
most citedTextBugger: Generating Adversarial Text Against Real-world Applications

333 citations · 595 across the 33 of their papers we have counts for

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11 papers · 1 filter

cs.CV20231 cited

Diff-ID: An Explainable Identity Difference Quantification Framework for DeepFake Detection

Chuer Yu, Xuhong Zhang, Yuxuan Duan +5

Despite the fact that DeepFake forgery detection algorithms have achieved impressive performance on known manipulations, they often face disastrous performance degradation when gen…

cs.CV2023

Watch Out for the Confusing Faces: Detecting Face Swapping with the Probability Distribution of Face Identification Models

Yuxuan Duan, Xuhong Zhang, Chuer Yu +3

Recently, face swapping has been developing rapidly and achieved a surprising reality, raising concerns about fake content. As a countermeasure, various detection approaches have b…

cs.CV2022

Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings

Yuhao Mao, Chong Fu, Saizhuo Wang +7

One intriguing property of adversarial attacks is their "transferability" -- an adversarial example crafted with respect to one deep neural network (DNN) model is often found effec…

cs.CV2021

Fine-Grained Fashion Similarity Prediction by Attribute-Specific Embedding Learning

Jianfeng Dong, Zhe Ma, Xiaofeng Mao +4

This paper strives to predict fine-grained fashion similarity. In this similarity paradigm, one should pay more attention to the similarity in terms of a specific design/attribute…

cs.CV202111 cited

Deep Dual Consecutive Network for Human Pose Estimation

Zhenguang Liu, Haoming Chen, Runyang Feng +4

Multi-frame human pose estimation in complicated situations is challenging. Although state-of-the-art human joints detectors have demonstrated remarkable results for static images,…

cs.CV202112 cited

Aggregated Multi-GANs for Controlled 3D Human Motion Prediction

Zhenguang Liu, Kedi Lyu, Shuang Wu +3

Human motion prediction from historical pose sequence is at the core of many applications in machine intelligence. However, in current state-of-the-art methods, the predicted futur…