Datasetpublic

rakshi719/GOT10k-I2V

GOT-10k Image-to-Video Retrieval MTEB/MOEB representation of the GOT-10k validation split for image-to-video retrieval. Task Given the first frame of a tracking sequence, retrieve the full tracking video. The mapping is one-to-one: each query has exactly one relevant item (the other direction of the same sequence). Contents Queries: 180 first-frame images Corpus: 180 tracking videos Qrels: 180 one-to-one binary relevance judgments… See the full description on the dataset page: https://huggingface.co/datasets/rakshi719/GOT10k-I2V.

sourceHugging Facecc-by-nc-sa-4.0updated 6d agoView on Hugging Face

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Dataset Card

GOT-10k Image-to-Video Retrieval

MTEB/MOEB representation of the GOT-10k validation split for image-to-video retrieval.

Task

Given the first frame of a tracking sequence, retrieve the full tracking video. The mapping is one-to-one: each query has exactly one relevant item (the other direction of the same sequence).

—Queries: 180 first-frame images
—Corpus: 180 tracking videos
—Qrels: 180 one-to-one binary relevance judgments

Source

GOT-10k (Generic Object Tracking benchmark) validation split — 180 real-world sequences spanning 563 object classes and 87 motion patterns. Videos are encoded from the official JPEG frames at 10 fps with libx264.

Paper: https://ieeexplore.ieee.org/document/8922619 Official site: http://got-10k.aitestunion.com/

License

CC-BY-4.0. See the official GOT-10k page for details.

Citation

bibtex

@article{huang2019got,
  author = {Lianghua Huang and Xin Zhao and Kaiqi Huang},
  title = {GOT-10k: A Large High-Diversity Benchmark for Generic Object
           Tracking in the Wild},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2019},
}