Author

Shui-Wang Li

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Preprint Sep 2026

Partition-Invariant Tuning for 3D Scene Understanding

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

#reinforcement learning Open access Sep 2026

Learning Adaptive Search with Reinforcement Learning for Small and Fast Object Tracking

The persistent challenge in visual object tracking, particularly for small and fast-moving targets, lies in the trade-off between effective resolution and contextual information. Fixed search regions cannot adapt to variations in target scale and motion, often resulting in degraded target representation and tracking fa...

Bin-Rui Liu, Xin-Yi Bo, Wen-Bin Luo et al. · Italian National Conference... · 0 citations

Review Open access Jul 2026

Foundation Models for Remote Sensing Semantic Segmentation: A Review of Architectures, Adaptations, and Prospects

This paper reviews recent progress from the perspectives of dataset evolution, model architectures, and downstream adaptation strategies, covering parameter-efficient fine-tuning, prompt engineering, few-shot and zero-shot learning, open-vocabulary segmentation, and domain adaptation.

Ming Deng, Yongyi Chen, Guanghai Ding et al. · Italian National Conference... · 0 citations

Preprint Jul 2026

SpikingMOT: A Spike-Driven Multi-Object Tracker

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