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arXiv AI By Sijia Chen, Shaofeng Liang, Lijuan Ma, Yanqiu Yu, Nan Li, Wenshuo Chen, Runwei Guan, Dongming Wu, En Yu, Yutao Yue

DRMOT: A Dataset and Framework for RGBD Referring Multi-Object Tracking

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The paper introduces DRMOT, a new dataset and framework for Referring Multi-Object Tracking (RMOT) that incorporates RGB-D data. DRSet contains 2,076 referring expressions across 186 RGB-D sequences, pairing synchronized RGB images, depth maps, and language descriptions—including depth-dependent cues—to evaluate spatial‑semantic detection and tracking. The proposed DRTrack framework uses a Geometric‑Aware GRPO fine‑tuned Multimodal Large Language Model to perform precise detection and robust trajectory association from joint language, RGB, and depth inputs, with experiments demonstrating its effectiveness.

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