Catherine R. He

EntityBench: Benchmark for Entity-Consistent Long-Range Multi-Shot Video Generation

EntityBench is a new benchmark comprising 140 episodes (2,491 shots) derived from real narrative media, designed to evaluate entity consistency—characters, objects, and locations—across long multi-shot video generation sequences. It introduces tiered difficulty up to 50 shots and recurrence gaps of up to 48 shots, paired with a three-pillar evaluation suite covering intra-shot quality, prompt alignment, and cross-shot consistency. The authors also propose EntityMem, a memory-augmented baseline that stores verified per-entity visual references in a persistent memory bank, achieving the highest character fidelity (Cohen's d = +2.33) among evaluated methods. Results show that cross-shot entity consistency degrades sharply with recurrence distance in existing approaches.