You can generate realistic novel views of mirror scenes by treating reflections as virtual views and using gated attention mechanisms—no retraining needed, just clever use of existing diffusion models.
This paper presents Ref-GeNVS, a method for generating novel views of scenes containing mirrors without requiring additional training. The key innovation is treating mirror reflections as complementary views by estimating the mirror plane and reflecting camera poses, then using a two-stage approach with special attention mechanisms to ensure reflections stay consistent during generation.