iClickSeg: Interactive click segmentation for zero-shot cross-category 3D part segmentation

doi:10.1016/j.patcog.2025.112816

iClickSeg: Interactive click segmentation for zero-shot cross-category 3D part segmentation

2025-12-01

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DOI：10.1016/j.patcog.2025.112816

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3D part segmentation is a crucial task for various applications, including robotics and shape analysis. Despite advancements in data-driven approaches, supervised methods heavily rely on annotated data, limiting their effectiveness in open-world scenarios and handling out-of-distribution test shapes. To address these challenges, we propose a novel interactive Click Segmentation (iClickSeg) method that achieves zero-shot cross-category 3D part segmentation via an iterative user interaction way. Specifically, our approach simulates user interactions through positive and negative clicks to guide the segmentation process, focusing on regions of interest and allowing for iterative refinement. To achieve this goal, we design a click sampling strategy learn shape-based prior information from point cloud data, enabling better feature encoding between points. Under the learned shape prior, the segmentation model can maintain the topology consistency and boost the performance with a simple PointNet++ network incorporation. For better refinement, we also present a post-processing strategy using outlier removal and heuristic click for obtaining the smooth segments. Extensive experiments on PartNet, PartNetE and S3DIS datasets demonstrate the superiority of iClickSeg over category-level segmentation methods and zero-shot methods. Inference tests on the AKB-48 data further validate the method's effectiveness and practicality in real-world scenarios.

Keywords:

Part segmentation

Cross-category understanding

Interactive segmentation

iClickSeg: Interactive click segmentation for zero-shot cross-category 3D part segmentation

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