SiamMOT is a region-based Siamese multi-object tracking network that simultaneously detects and associates object instances across video frames. It includes a motion model that estimates instance movement between frames to enable association of detections. The project provides two tracker variants—one with implicit motion modeling and one with explicit motion modeling—and experiments on MOT17, TAO-person, and Caltech Roadside Pedestrians datasets. Inference runs at 17 FPS for 720P video on a single modern GPU.