WHU-USI3DV / CoFiI2P

[IEEE RA-L 2024 & ICRA'25] CoFiI2P: Coarse-to-Fine Correspondences-Based Image-to-Point Cloud Registration
https://whu-usi3dv.github.io/CoFiI2P/
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Low Refine Correct Rate #20

Open qsisi opened 2 weeks ago

qsisi commented 2 weeks ago

I add the following lines to evaluate the refine correct rate of the fine module:

def lidar2uvs(xyz, lidar2cam, K):
  cam_pts = (lidar2cam[:3, :3] @ xyz.T + lidar2cam[:3, 3:]).T
  cam_pts = cam_pts / cam_pts[:, 2:]
  uvs = (K @ cam_pts.T).T
  uvs = uvs[:, :2]
  return uvs
gt_uvs = lidar2uvs(coarse_pc_points.cpu().numpy(), P, K.cpu().numpy())
coarse_uvs = fine_center_xy.T.cpu().numpy()
refine_uvs = fine_xy.T.cpu().numpy()
refine_correct = (np.linalg.norm(gt_uvs - refine_uvs, axis=-1) < np.linalg.norm(gt_uvs - coarse_uvs, axis=-1))

The mean refine_correct rate for over 5583 samples on the KITTI test set is 0.3325, which is pretty low in my understanding.

Could you provide some hints about it?