{
  "$type": "site.standard.document",
  "description": "A method for learning depth-aware keypoints and associated descriptors from monocular video for monocular visual odometry is described. The method includes training a keypoint network and a depth network to learn depth-aware keypoints and the associated descriptors. The training is based on a…",
  "path": "/patents/1296858",
  "publishedAt": "2021-08-05T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "B60W60/0027",
    "TOYOTA RESEARCH INSTITUTE, INC."
  ],
  "textContent": "A method for learning depth-aware keypoints and associated descriptors from monocular video for monocular visual odometry is described. The method includes training a keypoint network and a depth network to learn depth-aware keypoints and the associated descriptors. The training is based on a target image and a context image from successive images of the monocular video. The method also includes lifting 2D keypoints from the target image to learn 3D keypoints based on a learned depth map from the depth network. The method further includes estimating a trajectory of an ego-vehicle based on the learned 3D keypoints.",
  "title": "SELF-SUPERVISED 3D KEYPOINT LEARNING FOR MONOCULAR VISUAL ODOMETRY"
}