Xiamen University and NTU propose RoTA-Bench: interactive projection alignment benchmark for 3D pose reasoning

A team from Xiamen University and Nanyang Technological University proposed RoTA-Bench, which uses interactive 3D-to-2D projection alignment to evaluate whether vision-language models can precisely adjust an object's 3D pose based on visual feedback. The benchmark contains 674 tasks, of which 100 form a frozen test set; models must choose among 24 discrete rotation actions so that the projection reaches an IoU of 0.90 with the target contour.