nyu-visionx/

VSI-SUPER-Count

Website | Paper | GitHub | Models Authors: Shusheng Yang*, Jihan Yang*, Pinzhi Huang†, Ellis Brown†, et al. VSI-SUPER-Count is a benchmark for testing continual counting capabilities across changing viewpoints and scenes in arbitrarily long videos. It challenges models to maintain accurate object counts as new objects appear throughout extended video sequences.

VSI-SUPER-Count evaluates spatial supersensing by testing whether models can:

Count… See the full description on the dataset page: https://huggingface.co/datasets/nyu-visionx/VSI-SUPER-Count.