# Semantic Segmentation on FoodSeg154 Asian food set 1.0 (test)

Source: [Semantic Segmentation on FoodSeg154 Asian food set 1.0 (test)](<https://www.sota2.com/research/sota/semantic-segmentation-on-foodseg154-asian-food-set-1-0-test>)

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

Data updated: 2026-02-26T06:10:13.254Z

Evaluation of Semantic Segmentation performance on the test split of the FoodSeg154 Asian food set 1.0 dataset, reporting mIoU, mAcc, and aAcc.

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 Segmentation |
| Dataset (including any stated split) | FoodSeg154 Asian food set 1.0 (test) |
| Metric | mIoU |
| 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

- [mIoU](<https://www.sota2.com/research/sota/semantic-segmentation-on-foodseg154-asian-food-set-1-0-test.md?metric=mIoU>): Higher is better; unit: PERCENT.

- [mAcc](<https://www.sota2.com/research/sota/semantic-segmentation-on-foodseg154-asian-food-set-1-0-test.md?metric=mAcc>): Higher is better; unit: PERCENT.

- [aAcc](<https://www.sota2.com/research/sota/semantic-segmentation-on-foodseg154-asian-food-set-1-0-test.md?metric=aAcc>): Higher is better; unit: PERCENT.

## Recorded results

| Method | mIoU | Result date | Report paper |
| --- | --- | --- | --- |
| ReLeM-CCNet | 47.1 | Not recorded | 68fa69f01e209131cea25165 |
| CCNet | 41.3 | Not recorded | 68fa69f01e209131cea25165 |
| ReLeM-FPN | 30.8 | Not recorded | 68fa69f01e209131cea25165 |
| ReLeM-CCNet | 29.2 | Not recorded | 68fa69f01e209131cea25165 |
| CCNet | 28.6 | Not recorded | 68fa69f01e209131cea25165 |
| FPN | 27.1 | Not recorded | 68fa69f01e209131cea25165 |
| ReLeM-FPN | 22.9 | Not recorded | 68fa69f01e209131cea25165 |
| FPN | 21.9 | Not recorded | 68fa69f01e209131cea25165 |

### ReLeM-CCNet

mIoU: 47.1. Result ID: 698df7c3ffc3901de099d204.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f01e209131cea25165.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69f01e209131cea25165.md>)

[Implementation](<https://xiongweiwu.github.io/foodseg103.html>)

Recorded evaluation configuration: {"fine-tuned on Asian food set":true,"evaluation classes":112}. This record does not assert independent reproduction.

### CCNet

mIoU: 41.3. Result ID: 698df7c3ffc3901de099d203.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f01e209131cea25165.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa67ef1e209131cea193bd.md>)

[Implementation](<https://github.com/speedinghzl/CCNet>)

Recorded evaluation configuration: {"fine-tuned on Asian food set":true,"evaluation classes":112}. This record does not assert independent reproduction.

### ReLeM-FPN

mIoU: 30.8. Result ID: 698df7c3ffc3901de099d208.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f01e209131cea25165.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69f01e209131cea25165.md>)

[Implementation](<https://xiongweiwu.github.io/foodseg103.html>)

Recorded evaluation configuration: {"fine-tuned on Asian food set":true,"evaluation classes":112}. This record does not assert independent reproduction.

### ReLeM-CCNet

mIoU: 29.2. Result ID: 698df7c3ffc3901de099d202.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f01e209131cea25165.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69f01e209131cea25165.md>)

[Implementation](<https://xiongweiwu.github.io/foodseg103.html>)

Recorded evaluation configuration: {"fine-tuned on Asian food set":false,"evaluation classes":62}. This record does not assert independent reproduction.

### CCNet

mIoU: 28.6. Result ID: 698df7c3ffc3901de099d201.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f01e209131cea25165.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa67ef1e209131cea193bd.md>)

[Implementation](<https://github.com/speedinghzl/CCNet>)

Recorded evaluation configuration: {"fine-tuned on Asian food set":false,"evaluation classes":62}. This record does not assert independent reproduction.

### FPN

mIoU: 27.1. Result ID: 698df7c3ffc3901de099d207.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f01e209131cea25165.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa65a41e209131cea0b8b3.md>)

[Implementation](<https://github.com/facebookresearch/detectron>)

Recorded evaluation configuration: {"fine-tuned on Asian food set":true,"evaluation classes":112}. This record does not assert independent reproduction.

### ReLeM-FPN

mIoU: 22.9. Result ID: 698df7c3ffc3901de099d206.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f01e209131cea25165.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69f01e209131cea25165.md>)

[Implementation](<https://xiongweiwu.github.io/foodseg103.html>)

Recorded evaluation configuration: {"fine-tuned on Asian food set":false,"evaluation classes":62}. This record does not assert independent reproduction.

### FPN

mIoU: 21.9. Result ID: 698df7c3ffc3901de099d205.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69f01e209131cea25165.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa65a41e209131cea0b8b3.md>)

[Implementation](<https://github.com/facebookresearch/detectron>)

Recorded evaluation configuration: {"fine-tuned on Asian food set":false,"evaluation classes":62}. This record does not assert independent reproduction.

Page 1 of 1. This is an index page, not the full collection.