SVCBench: A Streaming Video Counting Benchmark for Spatial-Temporal State Maintenance
Video understanding requires models to continuously track and update world state during playback. Although existing benchmarks have advanced video understanding evaluation across multiple dimensions, they provide limited visibility into how models maintain world state over time. We propose SVCBench, a Streaming Video Counting Benchmark that repositions counting as a minimal, controlled probe for diagnosing models' world-state maintenance capability. We decompose this capability into object counting and event counting, forming 8 fine-grained subcategories. Object counting covers tracking currently visible objects and cumulative unique identities, while event counting covers detecting insta...
| Authors | Pengyiang Liu, Zhongyue Shi, Hongye Hao et al. |
|---|---|
| Primary category | cs.CV |
| Published | 13 March 2026 |
| Last updated at source | 29 June 2026 |
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