Dororo99/Ours_Waymo_ArmGS

OursWaymoArmGS

ArmGS checkpoints trained for dynamic urban novel-view synthesis on the Waymo Open Dataset.

License and required notice

This model was made using the Waymo Open Dataset, provided by Waymo LLC under the Waymo Dataset License Agreement for Non-Commercial Use. Access, use, redistribution, and modification of this model are governed by that agreement, including its non-commercial restrictions.

Read WAYMO_DATASET_LICENSE_NOTICE.md, the included archived agreement, and the current official terms before downloading or using these files. These checkpoints must not be used in vehicle operation, production systems, or primarily commercial applications.

Release contents

• —Nine completed 30,000-step training-split runs under waymo/<sequence>/splatad_30k/.
• —One completed 30,000-step validation reference under waymo/10448102132863604198_472_000_492_000/paper_reference_30k/.
• —Every released run includes checkpoints/final.pt, the resolved YAML, run metadata, W&B run identity, and final novel-view/reconstruction metric JSON files.
• —7566697458525030390_1440_000_1460_000 is not included yet because its 30,000-step training was still running when this release was packaged.

The nine training-split runs use the streetgs-periodic split, PAPER_MODE=0, and Waymo GT lidar_box actor tracking fallback. They must not be described as official SplatAD LINSPACE50 results. The separate validation reference uses CAStrack and centered known-pose COLMAP preprocessing.

See release_manifest.json for exact sequence IDs, checkpoint sizes, W&B IDs, and protocol metadata.

Loading

These are full PyTorch trainer checkpoints produced by the ArmGS implementation, not standalone safetensors weights. Use the matching ArmGS code and the included resolved config. As with any pickle-based PyTorch checkpoint, only load files obtained from a trusted source.

import torch

checkpoint = torch.load("waymo/<sequence>/splatad_30k/checkpoints/final.pt", map_location="cpu")
print(checkpoint["trainer"]["step"])

Citation

@misc{waymo_open_dataset,
  title   = {Waymo Open Dataset: An autonomous driving dataset},
  website = {https://www.waymo.com/open},
  year    = {2019--2025}
}