Abstract: Aspects of the disclosure relate to controlling a vehicle. For instance, using a camera, a first camera image including a first object may be captured. A first bounding box for the first object and a distance to the first object may be identified. A second camera image including a second object may be captured. A second bounding box for the second image and a distance to the second object may be identified. Whether the first object is the second object may be determined using a plurality of models to compare visual similarity of the two bounding boxes, to compare a three-dimensional location based on the distance to the first object and a three-dimensional location based on the distance to the second object, and to compare results from the first and second models. The vehicle may be controlled in an autonomous driving mode based on a result of the third model.

Abstract: Techniques are provided for generating depth estimates for pixels, in a series of images captured by a single camera, that correspond to the static objects. The techniques involve identifying occlusion events in the series of images. The occlusion events are events in which dynamic blobs are at least partially occluded, by static objects, from view of the camera. The depth estimates for pixels of the static objects are generated based on the occlusion events and depth estimates associated with the dynamic blobs. Techniques are also provided for generating the depth estimates associated with the dynamic blobs. The depth estimates for the dynamic blobs are generated based on how far down, within at least one image, the lowest point of the dynamic blob is located.