# Multi-label Image Classification on Shankar et al.

Source: [Multi-label Image Classification on Shankar et al.](<https://www.sota2.com/research/sota/multi-label-image-classification-on-shankar-et-al>)

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

Data updated: 2026-02-26T06:06:57.247Z

Evaluation of Multi-label Image Classification performance on the Shankar et al. dataset, typically measured using Top-1 Accuracy.

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 | Multi-label Image Classification |
| Dataset (including any stated split) | Shankar et al. |
| Metric | Top-1 Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 4 of 4 |
| 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/multi-label-image-classification-on-shankar-et-al.md?metric=Top-1%20Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Top-1 Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| ReLabel | 86.1 | Not recorded | 68fa6a751e209131cea2842b |
| Original | 85.3 | Not recorded | 68fa6a751e209131cea2842b |
| Label cleaning | 85.2 | Not recorded | 68fa6a751e209131cea2842b |
| Label smoothing | 84.7 | Not recorded | 68fa6a751e209131cea2842b |

### ReLabel

Top-1 Accuracy: 86.1. Result ID: 698e3724ffc3901de09bba3a.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6a751e209131cea2842b.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6a751e209131cea2842b.md>)

[Implementation](<https://github.com/naver-ai/relabel_imagenet>)

Recorded evaluation configuration: {"Network":"ResNet-50","Supervision":"ReLabel"}. This record does not assert independent reproduction.

### Original

Top-1 Accuracy: 85.3. Result ID: 698e3724ffc3901de09bba37.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6a751e209131cea2842b.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa61b41e209131ce9f58d2.md>)

Recorded evaluation configuration: {"Network":"ResNet-50","Supervision":"Original"}. This record does not assert independent reproduction.

### Label cleaning

Top-1 Accuracy: 85.2. Result ID: 698e3724ffc3901de09bba39.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6a751e209131cea2842b.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa67ba1e209131cea18229.md>)

Recorded evaluation configuration: {"Network":"ResNet-50","Supervision":"Label cleaning"}. This record does not assert independent reproduction.

### Label smoothing

Top-1 Accuracy: 84.7. Result ID: 698e3724ffc3901de09bba38.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6a751e209131cea2842b.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa62331e209131ce9f8333.md>)

Recorded evaluation configuration: {"Network":"ResNet-50","Supervision":"Label smoothing (ε=0.1)"}. This record does not assert independent reproduction.

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