95 citations · 362 across the 17 of their papers we have counts for
9 papers · 1 filter
Toward Open-World Electroencephalogram Decoding Via Deep Learning: A Comprehensive Survey
Xun Chen, Chang Li, Aiping Liu +3
Electroencephalogram (EEG) decoding aims to identify the perceptual, semantic, and cognitive content of neural processing based on non-invasively measured brain activity. Tradition…
AdaptPose: Cross-Dataset Adaptation for 3D Human Pose Estimation by Learnable Motion Generation
Mohsen Gholami, Bastian Wandt, Helge Rhodin +2
This paper addresses the problem of cross-dataset generalization of 3D human pose estimation models. Testing a pre-trained 3D pose estimator on a new dataset results in a major per…
Rethinking Crowdsourcing Annotation: Partial Annotation with Salient Labels for Multi-Label Image Classification
Jianzhe Lin, Tianze Yu, Z. Jane Wang
Annotated images are required for both supervised model training and evaluation in image classification. Manually annotating images is arduous and expensive, especially for multi-l…
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…
Distilling and Transferring Knowledge via cGAN-generated Samples for Image Classification and Regression
Xin Ding, Yongwei Wang, Zuheng Xu +2
Knowledge distillation (KD) has been actively studied for image classification tasks in deep learning, aiming to improve the performance of a student based on the knowledge from a…
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…