Visual Task Adaptation Benchmark (1000 examples per task).

Canonical transfer-learning benchmark covering 19 diverse vision tasks (natural, specialized, structured). Each task provides only 1000 labeled examples to test how well pretrained representations transfer to new domains with limited data.

Best published scores.

No results indexed yet — be the first to submit a score.

Primary

mean_accuracy · higher is better

Have a score that beats
this table?

Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.

• 01A public checkpoint or API endpoint
• 02A reproduction script with frozen commit + seed
• 03Declared evaluation environment (Python, deps)
• 04One row per metric declared by this dataset
• 05A contact so we can follow up on discrepancies