{
  "$type": "site.standard.document",
  "description": "A method for self-supervised depth and ego-motion estimation is described. The method includes determining a multi-camera photometric loss associated with a multi-camera rig of an ego vehicle. The method also includes generating a self-occlusion mask by manually segmenting self-occluded areas of…",
  "path": "/patents/1327615",
  "publishedAt": "2022-09-22T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "G06T7/579",
    "TOYOTA RESEARCH INSTITUTE, INC."
  ],
  "textContent": "A method for self-supervised depth and ego-motion estimation is described. The method includes determining a multi-camera photometric loss associated with a multi-camera rig of an ego vehicle. The method also includes generating a self-occlusion mask by manually segmenting self-occluded areas of images captured by the multi-camera rig of the ego vehicle. The method further includes multiplying the multi-camera photometric loss with the self-occlusion mask to form a self-occlusion masked photometric loss. The method also includes training a depth estimation model and an ego-motion estimation model according to the self-occlusion masked photometric loss. The method further includes predicting a 360° point cloud of a scene surrounding the ego vehicle according to the depth estimation model and the ego-motion estimation model.",
  "title": "SELF-OCCLUSION MASKS TO IMPROVE SELF-SUPERVISED MONOCULAR DEPTH ESTIMATION IN MULTI-CAMERA SETTINGS"
}