Papers › PointMixer: MLP-Mixer for Point Cloud Understanding
PointMixer: MLP-Mixer for Point Cloud Understanding
Jaesung Choe, Chunghyun Park, Francois Rameau, Jaesik Park, In So Kweon
MLP-Mixer has newly appeared as a new challenger against the realm of CNNs and transformer. Despite its simplicity compared to transformer, the concept of channel-mixing MLPs and token-mixing MLPs achieves noticeable performance in visual recognition tasks. Unlike images, point clouds are inherently sparse, unordered and irregular, which limits the direct use of MLP-Mixer for point cloud understanding. In this paper, we propose PointMixer, a universal point set operator that facilitates information sharing among unstructured 3D points. By simply replacing token-mixing MLPs with a softmax function, PointMixer can "mix" features within/between point sets. By doing so, PointMixer can be broadly used in the network as inter-set mixing, intra-set mixing, and pyramid mixing. Extensive experiments show the competitive or superior performance of PointMixer in semantic segmentation, classification, and point reconstruction against transformer-based methods.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D Point Cloud Classification | ModelNet40 | PointMixer | Mean Accuracy | 91.4 | #52 of 111 | Archive leaderboard | report |
| 3D Point Cloud Classification | ModelNet40 | PointMixer | Number of params | 6.5M | #52 of 111 | Archive leaderboard | report |
| 3D Point Cloud Classification | ModelNet40 | PointMixer | Overall Accuracy | 93.6 | #52 of 111 | Archive leaderboard | report |
| Semantic Segmentation | S3DIS Area5 | PointMixer | Number of params | 6.5M | #27 of 61 | Archive leaderboard | report |
| Semantic Segmentation | S3DIS Area5 | PointMixer | mAcc | 77.4 | #27 of 61 | Archive leaderboard | report |
| Semantic Segmentation | S3DIS Area5 | PointMixer | mIoU | 71.4 | #27 of 61 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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