[KongchangAI]
Company

BlueVeta

An AI team focused on visual processing of product images. It developed the dedicated rotation detection model BlueVetaUpright, aiming to solve vertical visual tasks such as automatically straightening product photos.

Timeline (last 90 days)

Oct 13

BlueVetaUpright achieved 91.1% accuracy on a four-quadrant rotation detection task with 400 real product photos, while ChatGPT achieved 75.9%, a gap of 15.2 percentage points (95% confidence interval [+10.4, +20.0], Bootstrap resampling 10000 times clustered by source photo).

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Oct 13

The experiment used 400 real product photos, split into two independent batches of 200 each, with no shared source photos between the two batches, to rule out the risk of data leakage.

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Oct 13

The BlueVeta team explained that the fluctuation in ChatGPT's accuracy between the two batches is because the consumer chat interface does not provide a fixed model snapshot guarantee, and backend routing may change between sessions.

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Oct 13

The confidence interval of the test results for the first group of 200 photos touched zero and did not reach statistical significance; the team therefore built a second independent batch to verify.

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Oct 13

The complete experimental method, bucket breakdown and limitations are published at blueveta.com/upright/research, and the research paper is archived on Zenodo (DOI: 10.5281/zenodo.22975679).

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