Jiadong Li

Lite-SVO: Towards A Lightweight Self-Supervised Semantic Visual Odometry Exploiting Multi-Feature Sharing Architecture

Not relying on ground-truth data for training, self-supervised semantic visual odometry (SVO) has recently gained considerable attention. Within self-supervised SVO, feature representation inconsistency between semantic/depth and pose tasks presents a significant challenge, as it may disrupt cross-t…