OSTrack implements a one-stream architecture that combines feature learning and relation modeling for visual object tracking. The method uses transformer architecture to jointly process template and search image features, enabling end-to-end tracking without separate feature extraction and matching stages. It achieves state-of-the-art results on standard tracking benchmarks including LaSOT, GOT-10k, and UAV123.