PanoWorld: Real-World Panoramic Generation
- Published
- Source
- arXiv
- Paper number
- 596
- Field
- Computer Vision
- arXiv ID
- 2607.09661
Key points
- It uses the rotational equivariance of panoramic ERP to treat rotation as a geometric transform and model only translation explicitly.
- DPRC uses dense conditioning on panorama rays for accurate motion control, and GMA uses geometry-aware memory augmentation to maintain scene persistence.
- The World360 dataset contains 70K real UAV clips and 50K AirSim360 simulation clips, including multi-altitude flight trajectories.
- Compared with Matrix-3D, it improves FID from 27.64 to 16.93 at 720p, and it improves PSNR trajectory accuracy by 2 to 4 points.
- Real-time generation with causal forcing produces 161 frames in 8 seconds on a single H20 GPU, versus about 4 minutes and 48 seconds previously.
- A three-stage training pipeline progressively optimizes modeling, memory, and control.
Paper links
External research summaries. These are not HDATF publications or measured product results.