Datasets:

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nvidia

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PhysicalAI-Autonomous-Vehicles

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NVIDIA 48.5k

Hi, thank you for releasing this amazing wrok!

I am trying to visualize the GT future trajectory by projecting it onto the camera image, but the result looks incorrect (trajectory does not align with the road geometry in the image), even though the turning direction is roughly correct.

Here are the details of what I did:

Dataset & clip

Dataset: nvidia/PhysicalAI-Autonomous-Vehicles

clip_id: 9779bda5-60c3-4f09-8dad-8b7fca09b496

GT trajectory

I use ego_future_xyz and ego_future_xyz_world returned by load_physical_aiavdataset

According to the loader implementation:

ego_future_xyz is expressed in the ego-local frame at t0

ego_future_xyz_world is in the world frame

For visualization, I either:

Directly project ego_future_xyz onto the t0 camera frame, or

Transform ego_future_xyz_world from world → ego(t0) local using egomotion, then project

Camera frame

I use the camera frame decoded at t0 (the last frame returned by decode_images_from_timestamps)

Image resolution exactly matches intrinsics (1920×1080)

Intrinsics and extrinsics are loaded directly from the dataset calibration

Observed issue

The projected GT trajectory does not lie on the road surface in the image

The overall turning trend (e.g., left/right turn) looks correct, but the trajectory is systematically offset

Changing a constant ego offset (e.g., ±4–5 m in x) does not fix the issue

Ego reference test points (e.g., [10, 0, 0] in ego frame) project to reasonable image locations

Question

Is ego_future_xyz guaranteed to be expressed in the same ego reference frame used by camera extrinsics (i.e., the ego frame origin for sensor calibration)?

Is there any known offset between the ego reference used for trajectory labels (e.g., rear axle / vehicle center) and the ego frame used in SENSOR_EXTRINSICS?

Are there any known caveats when projecting GT trajectories onto raw camera images for this dataset?

If anyone has encountered a similar issue or has guidance on the correct reference frame alignment, I would really appreciate it.

Thanks!