arXiv Computer Vision September 18, 2026 By Xinyu Zhang, Junjie Chen, Jiawei Ge, Qianlong Li, Libin Ma, Baokun Pan, Yahui Luo

Grounded Product Understanding in Livestream Videos

Read the original on arXiv Computer Vision →

The paper introduces GPUB, a large-scale benchmark for grounded product understanding in e‑commerce livestream videos, featuring 3,000 livestreams, 31K fashion products, and multi‑moment temporal annotations. It defines three evaluation tasks, with the main task (GPrU) requiring simultaneous product identification and moment localization. Existing multimodal models perform poorly on GPrU, prompting the authors to develop UniPro, which improves performance by learning product‑aligned, temporally structured representations.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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TLive-Omni: An Omni-Modal Understanding Model for E-Commerce Live Streaming

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