activity
20242026
most citedPointMamba: A Simple State Space Model for Point Cloud Analysis

22 citations · 24 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Wat3R: Underwater 3D Geometry Learning without Annotations

Jiangwei Ren, Xingyu Jiang, Zijie Song +4

Estimating 3D geometry in underwater environments presents unique challenges due to light attenuation, scattering, and the absence of large-scale, high-quality 3D annotations. Pion…

cs.CV2025

NAUTILUS: A Large Multimodal Model for Underwater Scene Understanding

Wei Xu, Cheng Wang, Dingkang Liang +4

Underwater exploration offers critical insights into our planet and attracts increasing attention for its broader applications in resource exploration, national security, etc. We s…

cs.CV2024★ 1 cited

A Unified Framework for 3D Scene Understanding

Wei Xu, Chunsheng Shi, Sifan Tu +3

We propose UniSeg3D, a unified 3D scene understanding framework that achieves panoptic, semantic, instance, interactive, referring, and open-vocabulary segmentation tasks within a…

cs.CV2024★ 1 cited

Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis

Xin Zhou, Dingkang Liang, Wei Xu +4

Point cloud analysis has achieved outstanding performance by transferring point cloud pre-trained models. However, existing methods for model adaptation usually update all model pa…

cs.CV2024★ 22 cited

PointMamba: A Simple State Space Model for Point Cloud Analysis

Dingkang Liang, Xin Zhou, Wei Xu +5

Transformers have become one of the foundational architectures in point cloud analysis tasks due to their excellent global modeling ability. However, the attention mechanism has qu…