4 citations · 11 across the 4 of their papers we have counts for
4 papers
RiWNet: A moving object instance segmentation Network being Robust in adverse Weather conditions
Chenjie Wang, Chengyuan Li, Bin Luo +2
Segmenting each moving object instance in a scene is essential for many applications. But like many other computer vision tasks, this task performs well in optimal weather, but the…
Object Detection based on OcSaFPN in Aerial Images with Noise
Chengyuan Li, Jun Liu, Hailong Hong +5
Taking the deep learning-based algorithms into account has become a crucial way to boost object detection performance in aerial images. While various neural network representations…
U2-ONet: A Two-level Nested Octave U-structure with Multiscale Attention Mechanism for Moving Instances Segmentation
Chenjie Wang, Chengyuan Li, Bin Luo
Most scenes in practical applications are dynamic scenes containing moving objects, so segmenting accurately moving objects is crucial for many computer vision applications. In ord…
DymSLAM:4D Dynamic Scene Reconstruction Based on Geometrical Motion Segmentation
Chenjie Wang, Bin Luo, Yun Zhang +6
Most SLAM algorithms are based on the assumption that the scene is static. However, in practice, most scenes are dynamic which usually contains moving objects, these methods are no…