VISTA (Video Grounding) - Animal-Object: 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 animal-object interactions, 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-8B63.2
2VISTA CogVLM Grounding (checkpoint unspecified)60.3
3Qwen-VL-Chat54.8
4InternVL2.5-8B49.8
5MiniGPT-v247.4
6VISTA Sphinx-v2 (checkpoint unspecified)46.9
7VISTA MiMo-VL-7B (checkpoint unspecified)38.3
8LLaVA-Grounding-7B37.1
9Shikra-7B28.9
10Ferret-7B23.7

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