44 citations · 52 across the 9 of their papers we have counts for
6 papers · 1 filter
PVNet: Point-Voxel Interaction LiDAR Scene Upsampling Via Diffusion Models
Xianjing Cheng, Lintai Wu, Zuowen Wang +3
Accurate 3D scene understanding in outdoor environments heavily relies on high-quality point clouds. However, LiDAR-scanned data often suffer from extreme sparsity, severely hinder…
Text-to-Events: Synthetic Event Camera Streams from Conditional Text Input
Joachim Ott, Zuowen Wang, Shih-Chii Liu
Event cameras are advantageous for tasks that require vision sensors with low-latency and sparse output responses. However, the development of deep network algorithms using event c…
Event-Based Eye Tracking. AIS 2024 Challenge Survey
Zuowen Wang, Chang Gao, Zongwei Wu +36
This survey reviews the AIS 2024 Event-Based Eye Tracking (EET) Challenge. The task of the challenge focuses on processing eye movement recorded with event cameras and predicting t…
3ET: Efficient Event-based Eye Tracking using a Change-Based ConvLSTM Network
Qinyu Chen, Zuowen Wang, Shih-Chii Liu +1
This paper presents a sparse Change-Based Convolutional Long Short-Term Memory (CB-ConvLSTM) model for event-based eye tracking, key for next-generation wearable healthcare technol…
Exploiting Spatial Sparsity for Event Cameras with Visual Transformers
Zuowen Wang, Yuhuang Hu, Shih-Chii Liu
Event cameras report local changes of brightness through an asynchronous stream of output events. Events are spatially sparse at pixel locations with little brightness variation. W…
Understanding (Non-)Robust Feature Disentanglement and the Relationship Between Low- and High-Dimensional Adversarial Attacks
Zuowen Wang, Leo Horne
Recent work has put forth the hypothesis that adversarial vulnerabilities in neural networks are due to them overusing "non-robust features" inherent in the training data. We show…