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Xiaoxu Xu

3 accepted papers

2026

DBGroup: Dual-Branch Point Grouping for Weakly Supervised 3D Semantic Instance Segmentation

AAAI 2026technical

Weakly supervised 3D instance segmentation is essential for 3D scene understanding, especially as the growing scale of data and high annotation costs associated with fully supervised approaches. Existing methods primarily rely on two forms of weak supervision: one-thing-one-click annotations and bou

Cited by 0SourcePDFScholar
2024

3D Weakly Supervised Semantic Segmentation with 2D Vision-Language Guidance

ECCV 2024poster

"In this paper, we propose 3DSS-VLG, a weakly supervised approach for 3D Semantic Segmentation with 2D Vision-Language Guidance, an alternative approach that a 3D model predicts dense-embedding for each point which is co-embedded with both the aligned image and text spaces from the 2D vision-languag…

2024

LESS: Label-Efficient and Single-Stage Referring 3D Segmentation

NeurIPS 2024poster

Referring 3D Segmentation is a visual-language task that segments all points of the specified object from a 3D point cloud described by a sentence of query. Previous works perform a two-stage paradigm, first conducting language-agnostic instance segmentation then matching with given text query. Howe…