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Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion

12 Mar 2021CVPR 2021 1arXiv:2103.07074archive 2025-07-28

Shi Qiu, Saeed Anwar, Nick Barnes

Given the prominence of current 3D sensors, a fine-grained analysis on the basic point cloud data is worthy of further investigation. Particularly, real point cloud scenes can intuitively capture complex surroundings in the real world, but due to 3D data's raw nature, it is very challenging for machine perception. In this work, we concentrate on the essential visual task, semantic segmentation, for large-scale point cloud data collected in reality. On the one hand, to reduce the ambiguity in nearby points, we augment their local context by fully utilizing both geometric and semantic features in a bilateral structure. On the other hand, we comprehensively interpret the distinctness of the points from multiple resolutions and represent the feature map following an adaptive fusion method at point-level for accurate semantic segmentation. Further, we provide specific ablation studies and intuitive visualizations to validate our key modules. By comparing with state-of-the-art networks on three different benchmarks, we demonstrate the effectiveness of our network.

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Code

ShiQiu0419/BAAF-Net officialmentioned in papermentioned on GitHubtf report
ananyajana/baafnet_pytorch pytorch report

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Tasks

3D Semantic SegmentationSegmentationSemantic Segmentation

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
3D Semantic Segmentation SemanticKITTI BAAF-Net test mIoU 59.9% #21 of 45 Archive leaderboard report
Semantic Segmentation S3DIS BAAF-Net Mean IoU 72.2 #19 of 54 Archive leaderboard report
Semantic Segmentation S3DIS BAAF-Net Number of params N/A #19 of 54 Archive leaderboard report
Semantic Segmentation S3DIS BAAF-Net mAcc 83.1 #19 of 54 Archive leaderboard report
Semantic Segmentation S3DIS BAAF-Net oAcc 88.9 #19 of 54 Archive leaderboard report
Semantic Segmentation S3DIS Area5 BAAF-Net Number of params N/A #44 of 61 Archive leaderboard report
Semantic Segmentation S3DIS Area5 BAAF-Net mAcc 73.1 #44 of 61 Archive leaderboard report
Semantic Segmentation S3DIS Area5 BAAF-Net mIoU 65.4 #44 of 61 Archive leaderboard report
Semantic Segmentation S3DIS Area5 BAAF-Net oAcc 88.9 #44 of 61 Archive leaderboard report
Semantic Segmentation Semantic3D BAAF-Net mIoU 75.4% #6 of 17 Archive leaderboard report
Semantic Segmentation Semantic3D BAAF-Net oAcc 94.9% #6 of 17 Archive leaderboard report

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