# Semantic-based Part Segmentation on PartNet (In-distribution)

Source: [Semantic-based Part Segmentation on PartNet (In-distribution)](<https://www.sota2.com/research/sota/semantic-based-part-segmentation-on-partnet-in-distribution>)

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

Data updated: 2026-02-26T05:52:16.738Z

Evaluation of Semantic-based Part Segmentation performance on the in-distribution split of the PartNet dataset, typically measured using Mean Recall.

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.

| Scope | Recorded value |
| --- | --- |
| Task | Semantic-based Part Segmentation |
| Dataset (including any stated split) | PartNet (In-distribution) |
| Metric | Mean Recall |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 8 of 8 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [Mean Recall](<https://www.sota2.com/research/sota/semantic-based-part-segmentation-on-partnet-in-distribution.md?metric=Mean%20Recall>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Mean Recall | Result date | Report paper |
| --- | --- | --- | --- |
| AutoGPart | 0.357 | Not recorded | 68fa6c5a1e209131cea337d2 |
| Learning to Group | 0.352 | Not recorded | 68fa6c5a1e209131cea337d2 |
| Meta-learning | 0.351 | Not recorded | 68fa6c5a1e209131cea337d2 |
| MixStyle | 0.344 | Not recorded | 68fa6c5a1e209131cea337d2 |
| PartNet InstSeg | 0.339 | Not recorded | 68fa6c5a1e209131cea337d2 |
| WCSeg | 0.298 | Not recorded | 68fa6c5a1e209131cea337d2 |
| SGPN | 0.25 | Not recorded | 68fa6c5a1e209131cea337d2 |
| GSPN | 0.235 | Not recorded | 68fa6c5a1e209131cea337d2 |

### AutoGPart

Mean Recall: 0.357. Result ID: 698f08d73a6c314849f51c1f.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c5a1e209131cea337d2.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6c5a1e209131cea337d2.md>)

[Implementation](<https://autogpart.github.io/>)

Recorded evaluation configuration: {"Backbone":"PointNet++"}. This record does not assert independent reproduction.

### Learning to Group

Mean Recall: 0.352. Result ID: 698f08d73a6c314849f51c1d.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c5a1e209131cea337d2.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6aca1e209131cea2a45c.md>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### Meta-learning

Mean Recall: 0.351. Result ID: 698f08d73a6c314849f51c19.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c5a1e209131cea337d2.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa63b51e209131cea002c8.md>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### MixStyle

Mean Recall: 0.344. Result ID: 698f08d73a6c314849f51c18.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c5a1e209131cea337d2.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69ac1e209131cea233f3.md>)

[Implementation](<https://github.com/KaiyangZhou/mixstyle-release>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### PartNet InstSeg

Mean Recall: 0.339. Result ID: 698f08d73a6c314849f51c1a.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c5a1e209131cea337d2.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa65301e209131cea08bc3.md>)

[Implementation](<https://cs.stanford.edu/~kaichun/partnet/>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### WCSeg

Mean Recall: 0.298. Result ID: 698f08d73a6c314849f51c1e.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c5a1e209131cea337d2.md>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### SGPN

Mean Recall: 0.25. Result ID: 698f08d73a6c314849f51c1b.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c5a1e209131cea337d2.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa65db1e209131cea0cde1.md>)

[Implementation](<https://www.sota2.com/github.com/laughtervv/SGPN>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### GSPN

Mean Recall: 0.235. Result ID: 698f08d73a6c314849f51c1c.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c5a1e209131cea337d2.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa65331e209131cea08ddd.md>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

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