nyu-visionx/VSI-SUPER-Recall
VSI-SUPER-Recall Website | Paper | GitHub | Models Authors: Shusheng Yang*, Jihan Yang*, Pinzhi Huang†, Ellis Brown†, et al. VSI-SUPER-Recall is a benchmark for testing long-horizon spatial observation and recall in arbitrarily long videos. It evaluates whether models can remember and recall the order in which unusual objects appeared across extended video sequences. Overview VSI-SUPER-Recall challenges models to: Track object appearances across long videos… See the full description on the dataset page: https://huggingface.co/datasets/nyu-visionx/VSI-SUPER-Recall.
| Author / organization | nyu-visionx |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 469 (as reported by Hugging Face) |
| Likes | 5 |
| Created | 22 October 2025 |
| Last updated at source | 7 November 2025 |
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469 now (+36 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 17 Oct 2026 Description: VSI-SUPER-Recall Website | Paper | GitHub | Models Authors: Shusheng Yang*, Jihan Yang*, Pinzhi Huang†, Ellis Brown†, et al. VSI-SUPER-Recall is a benchmark for testing long-horizon spatial observation and recall in arbitrarily long videos. → VSI-SUPER-Recall Website | Paper | GitHub | Models Authors: Shusheng Yang*, Jihan Yang*, Pinzhi Huang†, Ellis Brown†, et al. VSI-SUPER-Recall is a benchmark for testing long-horizon spatial observation and recall in arbitrarily long videos.
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