5 papers · 1 filter
ByteAction: Byte-space Action Recognition Foundation Model
Fangcheng Li, Zhen Yu, Kejun Wu +2
Byte-space Action Recognition (BAR) aims to recognize human actions directly from compressed image bitstreams without any pixel decoding. By operating entirely in byte space, BAR i…
Bitstream Action Recognition is Byte Modeling
Fangcheng Li, Chaoran Huang, Tianyi Liu +5
Conventional action recognition typically relies on successful pixel decoding of the bitstream. However, bitstream corruption during storage or transmission may cause severe visual…
Dynamic Graph Neural Network with Adaptive Features Selection for RGB-D Based Indoor Scene Recognition
Qiong Liu, Ruofei Xiong, Xingzhen Chen +2
Multi-modality of color and depth, i.e., RGB-D, is of great importance in recent research of indoor scene recognition. In this kind of data representation, depth map is able to des…
Extending Depth of Field for Varifocal Multiview Images
Zhilong Li, Kejun Wu, Qiong Liu +1
Optical imaging systems are generally limited by the depth of field because of the nature of the optics. Therefore, extending depth of field (EDoF) is a fundamental task for meetin…
FSF-Net: Enhance 4D Occupancy Forecasting with Coarse BEV Scene Flow for Autonomous Driving
Erxin Guo, Pei An, You Yang +2
4D occupancy forecasting is one of the important techniques for autonomous driving, which can avoid potential risk in the complex traffic scenes. Scene flow is a crucial element to…