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20182022
most citedDeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms

52 citations · 196 across the 15 of their papers we have counts for

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7 papers · 1 filter

cs.CV2021

CarveNet: Carving Point-Block for Complex 3D Shape Completion

Qing Guo, Zhijie Wang, Felix Juefei-Xu +4

3D point cloud completion is very challenging because it heavily relies on the accurate understanding of the complex 3D shapes (e.g., high-curvature, concave/convex, and hollowed-o…

cs.CV2021

Learning to Adversarially Blur Visual Object Tracking

Qing Guo, Ziyi Cheng, Felix Juefei-Xu +4

Motion blur caused by the moving of the object or camera during the exposure can be a key challenge for visual object tracking, affecting tracking accuracy significantly. In this w…

cs.CV20212 cited

AdvFilter: Predictive Perturbation-aware Filtering against Adversarial Attack via Multi-domain Learning

Yihao Huang, Qing Guo, Felix Juefei-Xu +4

High-level representation-guided pixel denoising and adversarial training are independent solutions to enhance the robustness of CNNs against adversarial attacks by pre-processing…

cs.CV202134 cited

JPGNet: Joint Predictive Filtering and Generative Network for Image Inpainting

Qing Guo, Xiaoguang Li, Felix Juefei-Xu +3

Image inpainting aims to restore the missing regions of corrupted images and make the recovery result identical to the originally complete image, which is different from the common…

cs.CV20216 cited

Auto-Exposure Fusion for Single-Image Shadow Removal

Lan Fu, Changqing Zhou, Qing Guo +5

Shadow removal is still a challenging task due to its inherent background-dependent and spatial-variant properties, leading to unknown and diverse shadow patterns. Even powerful st…

cs.CV202052 cited

DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms

Hua Qi, Qing Guo, Felix Juefei-Xu +5

As the GAN-based face image and video generation techniques, widely known as DeepFakes, have become more and more matured and realistic, there comes a pressing and urgent demand fo…