Scene-level point cloud understanding remains challenging due to diverse geometries and spatial layouts. While pre-trained 3D point cloud foundation models (PFMs) offer strong transferability, full fine-tuning (FFT) incurs substantial computational and storage costs. Parameter-efficient fine-tuning (PEFT) provides a pr...
Hong-Qiang Lin, Tian-Le Wang, Shui-Wang Li et al.· 0 citations
MoSaiC, a novel Motion-Saliency Complementary masked modeling framework for self-supervised point cloud video representation learning, couples three components: Curriculum Motion-Saliency Masking (CMSM), which guides the masking process toward motion-salient tokens under a curriculum schedule; Normal-Flow Motion (NFM)...
Wei Wang, Yi-Ding Sun, Yuying Wang et al.· 0 citations
SpikingMOT is proposed as a spike-driven tracker that adaptively models sparse trajectory dynamics with spiking neural networks (SNNs) and brings SNNs into MOT, opening a promising direction for efficient tracking.
Yiding Sun, Xiangyang Yang, Dongxu Zhang et al.· 1 citation
This work proposes a simple yet effective framework called Anchor-guided adaptive inter-frame motion cues propagating (Again-Pose), reformulating pose estimation in degraded frames as a motion-guided recovery task, significantly outperforms state-of-the-art methods in robustness and stability.
Shuaikang Zhu, Yiding Sun, Yang Yang· arXiv.org· 0 citations
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