# Shape-Prior-Based Point Cloud Completion for Single-Stage Fully Sparse 3D Object Detection

Source: [Shape-Prior-Based Point Cloud Completion for Single-Stage Fully Sparse 3D Object Detection](<https://www.sota2.com/research/paper/6a1e63cadbd7150506f853fa>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-06-02T05:00:51.557Z

Authors: Kaizheng Wang, Mingqian Ji, Jian Yang, Shanshan Zhang

Published: 2026-05-30T11:49:58.000Z

## Abstract

Single-stage fully sparse 3D object detectors rely on point clouds data to detect objects in autonomous driving scenarios. However, the sparsity and incompleteness of point clouds significantly limit the performance of 3D object detection. To address this issue, this paper proposes a point clouds completion method specifically designed for single-stage fully sparse detectors. The entire shape-prior-based completion process consists of two consecutive steps. In the first step, we design a novel Instance Selection module, which is capable of identifying point clouds corresponding to foreground objects even when the baseline model does not generate proposals, while effectively ignoring the point clouds of background regions. In the second step, we introduce a novel Alignment-Based Point Completion module, which aligns the point clouds of foreground objects with prototypes in terms of both their centers and orientations. Subsequently, points are selected from the prototype to fill in the missing parts of the foreground object. We evaluated our method on two single-stage fully sparse detectors using the KITTI dataset. The experimental results demonstrate that the proposed method significantly improves the detection performance, confirming its effectiveness and generalizability.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [3D Object Detection on KITTI (test) (AP R40)](<https://www.sota2.com/research/sota/3d-object-detection-on-kitti-test-ap-r40.md>): 3D Object Detection; KITTI (test); Car Easy AP R40: 86.53.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2606.00688>)

[PDF](<https://arxiv.org/pdf/2606.00688.pdf>)