LAS2: Ultra-Fast Zero-Shot Stereo Matching Without Foundation Model Priors

Lite Any Stereo V2 achieves competitive zero-shot stereo matching generalization using a 2D-only cost aggregation framework optimized for real inference latency rather than theoretical MACs, targeting resource-constrained deployment. The architecture challenges the assumption that efficient stereo models cannot generalize well without large foundation model backbones.