Enhancing In-context Panoramic Generation via Geometric-aware Pretraining

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining

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…

Hugging Face · Daily Papers ·Haoran Feng, Ruiyang Zhang · ·▲ 14 upvotes

Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.

Autores: Haoran Feng, Ruiyang Zhang, Longyi Zhang, Dizhe Zhang, Lu Qi

  • 14 upvotes da comunidade
  • Temas: in-context panoramic generation, geometry-aware pretraining, downstream task-specific fine-tuning, panoramic image fidelity, parallel depth generation, velocity circular padding

Resumo

Resumo original (em inglês), extraído do paper:

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.

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