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PanoWorld proposes a method for long-range memory in panoramic world models using rotation-equivariant representations, with a three-stage training pipeline and a new large-scale dataset World360. The model outperforms alternatives by a large margin.
Canvas360 is a two-stage framework for in-context panoramic generation that combines geometry-aware pretraining with fine-tuning, featuring a large-scale dataset and novel modeling techniques for improved geometric consistency and global coherence.