VISTA (Video Grounding) - Human-Self: leaderboard

Metric: Mean spatio-temporal IoU (m_vIoU, %): per-frame box IoU summed over the frames where predicted and true tubes overlap in time, divided by their temporal union, on solitary human actions (human-self), over the 11,814 video-query pairs of VISTA (HCSTVG-v1 and v2, VidVRD, VidSTG, MeViS and RVOS videos re-annotated with an interaction taxonomy), zero-shot on sub-sampled frames; the model must localize the queried subject with a box in every frame; higher is better. Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 10 models tracked.

Top models

#ModelScore
1Qwen3-VL-8B75.7
2Qwen-VL-Chat58.8
3InternVL2.5-8B50.9
4VISTA Sphinx-v2 (checkpoint unspecified)48.1
5VISTA CogVLM Grounding (checkpoint unspecified)46.8
6MiniGPT-v246.4
7VISTA MiMo-VL-7B (checkpoint unspecified)46
8LLaVA-Grounding-7B38.9
9Shikra-7B38.8
10Ferret-7B33.6

Interactive version: theaggregate.ai/benchmark?slug=vista-video-grounding-human-self · How It Works · Data refreshed daily, snapshot 2026-10-07.