3 accepted papers
Recently, state space models (SSM), particularly Mamba, have attracted significant attention from scholars due to their ability to effectively balance computational efficiency and performance. However, most existing visual Mamba methods flatten images into 1D sequences using predefined scan orders,…
Accurate understanding of lunar surface topography is vital for effective decision-making and remote control of lunar rovers during exploration missions. Conventional sensing methods often struggle to capture the intricate details of the lunar landscape. In response, we propose an innovative approac…
In this paper, we focus on developing knowledge distillation (KD) for compact 3D detectors. We observe that off-the-shelf KD methods manifest their efficacy only when the teacher model and student counterpart share similar intermediate feature representations. This might explain why they are less ef…