Multiple stage image based object detection and recognition

One or more tangible, non-transitory computer-readable media storing computer-readable instructions that when executed by one or more processors cause the one or more processors to perform operations;

• the operations comprising:
• receiving object data comprising one or more portions of sensor data;
• determining, in a first stage of a multiple stage classification, one or more first stage characteristics of the one or more portions of sensor data based in part on a first machine-learned model, wherein the one or more first stage characteristics comprise an indication of whether at least one portion of the one or more portions of sensor data is foreground or background;
• determining, in a second stage of the multiple stage classification, one or more second stage characteristics and based on the one or more first stage characteristics determined in the first stage of the one or more portions of sensor data based in part on a second machine-learned model;
• and
• generating, an object output based in part on the one or more first stage characteristics and the one or more second stage characteristics, wherein the object output comprises one or more indications associated with detection of one or more objects in the one or more portions of sensor data, wherein the one or more second stage characteristics comprise an object classification of at least one foreground portion of the one or more portions of sensor data.

A computing system comprising

• one or more processors;
• and
• a memory comprising one or more computer-readable media, the memory storing computer-readable instructions that when executed by the one or more processors cause the one or more processors to perform operations comprising:
• receiving object data comprising one or more portions of sensor data;
• determining, in a first stage of a multiple stage classification using one or more hardware components, one or more first stage characteristics of the one or more portions of sensor data based in part on a first machine-learned model, wherein the one or more first stage characteristics comprise an indication of whether at least one portion of the one or more portions of sensor data is foreground or background;
• determining, in a second stage of the multiple stage classification and based on the one or more first stage characteristics determined in the first stage, one or more second stage characteristics of the one or more portions of sensor data based in part on a second machine-learned model;
• and
• generating, an object output based in part on the one or more first stage characteristics and the one or more second stage characteristics, wherein the object output comprises one or more indications associated with detection of one or more objects in the one or more portions of sensor data, wherein the one or more second stage characteristics comprise an object classification of at least one foreground portion of the one or more portions of sensor data.