102 citations · 197 across the 8 of their papers we have counts for
5 papers · 1 filter
Kernel Modulation: A Parameter-Efficient Method for Training Convolutional Neural Networks
Yuhuang Hu, Shih-Chii Liu
Deep Neural Networks, particularly Convolutional Neural Networks (ConvNets), have achieved incredible success in many vision tasks, but they usually require millions of parameters…
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…
v2e: From Video Frames to Realistic DVS Events
Yuhuang Hu, Shih-Chii Liu, Tobi Delbruck
To help meet the increasing need for dynamic vision sensor (DVS) event camera data, this paper proposes the v2e toolbox that generates realistic synthetic DVS events from intensity…
DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Prediction
Yuhuang Hu, Jonathan Binas, Daniel Neil +2
Neuromorphic event cameras are useful for dynamic vision problems under difficult lighting conditions. To enable studies of using event cameras in automobile driving applications,…
Learning to Exploit Multiple Vision Modalities by Using Grafted Networks
Yuhuang Hu, Tobi Delbruck, Shih-Chii Liu
Novel vision sensors such as thermal, hyperspectral, polarization, and event cameras provide information that is not available from conventional intensity cameras. An obstacle to u…