# Object Detection on Cars

Source: [Object Detection on Cars](<https://www.sota2.com/research/sota/object-detection-on-cars>)

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

Data updated: 2026-02-26T06:07:07.503Z

Evaluation of Object Detection performance on the Cars dataset.

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 | Object Detection |
| Dataset (including any stated split) | Cars |
| Metric | Top-1 Accuracy |
| 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

- [Top-1 Accuracy](<https://www.sota2.com/research/sota/object-detection-on-cars.md?metric=Top-1%20Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Top-1 Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| CCSSL | 92.47 | Not recorded | 6938fe646cfd488761a53adb |
| SimMatchV2 | 91.86 | Not recorded | 6938fe646cfd488761a53adb |
| CLOP | 91.71 | Not recorded | 6938fe646cfd488761a53adb |
| SupCon | 91.69 | Not recorded | 6938fe646cfd488761a53adb |
| SimCLR | 91.3 | Not recorded | 6938fe646cfd488761a53adb |
| SimMatch | 91.27 | Not recorded | 6938fe646cfd488761a53adb |
| SsCL | 90.89 | Not recorded | 6938fe646cfd488761a53adb |
| FixMatch | 90.04 | Not recorded | 6938fe646cfd488761a53adb |

### CCSSL

Top-1 Accuracy: 92.47. Result ID: 6995ea343badfaffe6f2e23a.

[Reporting paper](<https://www.sota2.com/research/paper/6938fe646cfd488761a53adb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6d6b1e209131cea39b40.md>)

[Implementation](<https://github.com/TencentYoutuResearch/Classification-SemiCLS>)

Recorded evaluation configuration: {"Pre-trained":"ImageNet","Backbone":"ResNet-50 (4x)","Evaluation Protocol":"fine-tune"}. This record does not assert independent reproduction.

### SimMatchV2

Top-1 Accuracy: 91.86. Result ID: 6995ea343badfaffe6f2e23c.

[Reporting paper](<https://www.sota2.com/research/paper/6938fe646cfd488761a53adb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa70591e209131cea4a78d.md>)

[Implementation](<https://github.com/mingkai-zheng/SimMatchV2>)

Recorded evaluation configuration: {"Pre-trained":"ImageNet","Backbone":"ResNet-50 (4x)","Evaluation Protocol":"fine-tune"}. This record does not assert independent reproduction.

### CLOP

Top-1 Accuracy: 91.71. Result ID: 6995ea343badfaffe6f2e23d.

[Reporting paper](<https://www.sota2.com/research/paper/6938fe646cfd488761a53adb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/6938fe646cfd488761a53adb.md>)

Recorded evaluation configuration: {"Pre-trained":"ImageNet","Backbone":"ResNet-50 (4x)","Evaluation Protocol":"fine-tune"}. This record does not assert independent reproduction.

### SupCon

Top-1 Accuracy: 91.69. Result ID: 6995ea343badfaffe6f2e237.

[Reporting paper](<https://www.sota2.com/research/paper/6938fe646cfd488761a53adb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa697f1e209131cea22756.md>)

Recorded evaluation configuration: {"Pre-trained":"ImageNet","Backbone":"ResNet-50 (4x)","Evaluation Protocol":"fine-tune"}. This record does not assert independent reproduction.

### SimCLR

Top-1 Accuracy: 91.3. Result ID: 6995ea343badfaffe6f2e236.

[Reporting paper](<https://www.sota2.com/research/paper/6938fe646cfd488761a53adb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa67d71e209131cea18de5.md>)

[Implementation](<https://github.com/google-research/simclr>)

Recorded evaluation configuration: {"Pre-trained":"ImageNet","Backbone":"ResNet-50 (4x)","Evaluation Protocol":"fine-tune"}. This record does not assert independent reproduction.

### SimMatch

Top-1 Accuracy: 91.27. Result ID: 6995ea343badfaffe6f2e23b.

[Reporting paper](<https://www.sota2.com/research/paper/6938fe646cfd488761a53adb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6c0c1e209131cea31a70.md>)

[Implementation](<https://github.com/KyleZheng1997/simmatch>)

Recorded evaluation configuration: {"Pre-trained":"ImageNet","Backbone":"ResNet-50 (4x)","Evaluation Protocol":"fine-tune"}. This record does not assert independent reproduction.

### SsCL

Top-1 Accuracy: 90.89. Result ID: 6995ea343badfaffe6f2e239.

[Reporting paper](<https://www.sota2.com/research/paper/6938fe646cfd488761a53adb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69f51e209131cea25417.md>)

Recorded evaluation configuration: {"Pre-trained":"ImageNet","Backbone":"ResNet-50 (4x)","Evaluation Protocol":"fine-tune"}. This record does not assert independent reproduction.

### FixMatch

Top-1 Accuracy: 90.04. Result ID: 6995ea343badfaffe6f2e238.

[Reporting paper](<https://www.sota2.com/research/paper/6938fe646cfd488761a53adb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa68d61e209131cea1e896.md>)

Recorded evaluation configuration: {"Pre-trained":"ImageNet","Backbone":"ResNet-50 (4x)","Evaluation Protocol":"fine-tune"}. This record does not assert independent reproduction.

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