38 citations · 49 across the 7 of their papers we have counts for
13 papers
Occlusion-Robust FAU Recognition by Mining Latent Space of Masked Autoencoders
Minyang Jiang, Yongwei Wang, Martin J. McKeown +1
Facial action units (FAUs) are critical for fine-grained facial expression analysis. Although FAU detection has been actively studied using ideally high quality images, it was not…
Delving into Deep Image Prior for Adversarial Defense: A Novel Reconstruction-based Defense Framework
Li Ding, Yongwei Wang, Xin Ding +4
Deep learning based image classification models are shown vulnerable to adversarial attacks by injecting deliberately crafted noises to clean images. To defend against adversarial…
TriPose: A Weakly-Supervised 3D Human Pose Estimation via Triangulation from Video
Mohsen Gholami, Ahmad Rezaei, Helge Rhodin +2
Estimating 3D human poses from video is a challenging problem. The lack of 3D human pose annotations is a major obstacle for supervised training and for generalization to unseen da…
Multi-view 3D Reconstruction with Transformer
Dan Wang, Xinrui Cui, Xun Chen +5
Deep CNN-based methods have so far achieved the state of the art results in multi-view 3D object reconstruction. Despite the considerable progress, the two core modules of these me…
Adversarial Attacks on Camera-LiDAR Models for 3D Car Detection
Mazen Abdelfattah, Kaiwen Yuan, Z. Jane Wang +1
Most autonomous vehicles (AVs) rely on LiDAR and RGB camera sensors for perception. Using these point cloud and image data, perception models based on deep neural nets (DNNs) have…
Towards Universal Physical Attacks On Cascaded Camera-Lidar 3D Object Detection Models
Mazen Abdelfattah, Kaiwen Yuan, Z. Jane Wang +1
We propose a universal and physically realizable adversarial attack on a cascaded multi-modal deep learning network (DNN), in the context of self-driving cars. DNNs have achieved h…