3 accepted papers
The ability to adapt to varying observation lengths is crucial for human trajectory prediction tasks, particularly in scenarios with limited observation lengths or missing data. Existing approaches mainly focus on introducing novel architectures or additional structural components, which substantial…
Algorithm of outlier removal for learning-based 3D point cloud registration is usually regarded as a classification problem. The core for this to be successful is to learn the discriminative inlier/outlier feature representations. This letter proposes a two-stage efficient network (MuSCLe-Reg) with
Trajectory prediction is a critical technique for autonomous driving, robot navigation and intelligent surveillance. The recurrent neural networks (RNNs) models propagate temporal information through hidden states and have been widely applied in adapting to varying input lengths and generating multi