AIIC AI Intelligence Centre

SOURCE-LINKED INTELLIGENCE

OmniVBench: A Benchmark and Large-Scale Dataset for Omni Reference-to-Video Generation

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

Reference-to-video (R2V) generation is evolving toward increasingly general and versatile reference control, giving rise to the emerging paradigm of omni R2V generation. However, existing benchmarks fall short of these emerging capabilities: their test cases cover limited reference types and compositions, and their evaluation protocols largely assess holistic reference consistency, overlooking whether reference factors are properly preserved, disentangled, and routed. Meanwhile, the high cost of constructing omni R2V training data makes suitable training resources scarce. To address these gaps

Read original source ↗ Open in workspace

recordType
paper
region
Global

Evidence & attribution

First collected: 2026-09-23T13:51:27.104Z. This is not the publication date.