Object detection neural networks

A system comprising:

• one or more computers;
• and
• a non-transitory computer-readable medium coupled to the one or more computers having instructions stored thereon, which, when executed by the one or more computers, cause the one or more computers to perform operations comprising:
• processing, by one or more computers, a first input generated from first sensor data collected by one or more first sensors of a vehicle using a first high-recall object detection neural network, wherein the first sensor data characterizes an environment in a vicinity of the vehicle, and wherein the first high-recall object detection neural network is configured to:
• receive the first input;
• and
• process the first input to generate:
• for each of a plurality of bounding boxes that each correspond to a respective region of the environment, a respective first confidence score that represents a probability that an object is present in the region of the environment corresponding to the bounding box;
• selecting, based at least on the respective first confidence scores, a first region of the environment corresponding to a first bounding box of the plurality of bounding boxes;
• in response to selecting the first region:
• obtaining, by the one or more computers, a second input characterizing the first region of an environment, the second input comprising data generated from second sensor data collected by one or more second sensors of the vehicle;
• and
• processing, by the one or more computers, the second input using a high precision object detection neural network to generate a respective object score for each object category in a set of one or more object categories, wherein each object score represents a respective probability that an object belonging to the object category is present in the first region of the environment.

A non-transitory computer storage device encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:

• processing, by one or more computers, a first input generated from first sensor data collected by one or more first sensors of a vehicle using a first high-recall object detection neural network, wherein the first sensor data characterizes an environment in a vicinity of the vehicle, and wherein the first high-recall object detection neural network is configured to:
• receive the first input;
• and
• process the first input to generate:
• for each of a plurality of bounding boxes that each correspond to a respective region of the environment, a respective first confidence score that represents a probability that an object is present in the region of the environment corresponding to the bounding box;
• selecting, based at least on the respective first confidence scores, a first region of the environment corresponding to a first bounding box of the plurality of bounding boxes;
• in response to selecting the first region:
• obtaining, by the one or more computers, a second input characterizing the first region of an environment, the second input comprising data generated from second sensor data collected by one or more second sensors of the vehicle;
• and
• processing, by the one or more computers, the second input using a high precision object detection neural network to generate a respective object score for each object category in a set of one or more object categories, wherein each object score represents a respective probability that an object belonging to the object category is present in the first region of the environment.