BeyondMasks: Evaluating Causal and Physical Consistency in Video Object Removal
Recent advances in generative video models have significantly improved visual realism in video object removal, yet evaluation protocols still focus on masked region fidelity, treating removal as local inpainting. In real scenes, object removal is a causal intervention: eliminating an object also requires removing its induced physical effects, such as shadows, reflections, illumination changes, translucency, and dynamic traces. Existing benchmarks lack aligned clean references or remain limited to simplified synthetic settings, preventing systematic evaluation of causal consistency. We introduce BeyondMasks, a paired benchmark for causally consistent video object removal, consisting of tem...
| Authors | Yigit Ekin, Enes Sanli, Aykut Erdem et al. |
|---|---|
| Primary category | cs.CV |
| Published | 20 August 2026 |
| Last updated at source | 20 August 2026 |
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