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arXiv Computer Vision By Ge Luo, Changhuo Yang, Weisi Fan, Rui Yang, Shaokai Wang

Beyond a Single Crop: Contextualized Embeddings for Player Re-Identification

Read the original on arXiv Computer Vision →

The paper introduces ContextReID, a framework that generates player embeddings by incorporating contextual information from co-occurring players in the same frame and from multiple frames in a broadcast sequence. Unlike traditional single-crop methods, this approach uses a vision‑language model to produce context‑aware embeddings that capture cross‑frame identity relationships. Experiments on three multi‑object tracking benchmarks demonstrate that ContextReID outperforms conventional single‑crop embeddings in Rank‑1 and mAP metrics for player re‑identification.

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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