Video Visual Relation Detection

@inproceedings{Shang2017VideoVR,
  title={Video Visual Relation Detection},
  author={Xindi Shang and Tongwei Ren and Jingfan Guo and Hanwang Zhang and Tat-Seng Chua},
  booktitle={ACM Multimedia},
  year={2017}
}
As a bridge to connect vision and language, visual relations between objects in the form of relation triplet $łangle subject,predicate,object\rangle$, such as "person-touch-dog'' and "cat-above-sofa'', provide a more comprehensive visual content understanding beyond objects. In this paper, we propose a novel vision task named Video Visual Relation Detection (VidVRD) to perform visual relation detection in videos instead of still images (ImgVRD). As compared to still images, videos provide a… CONTINUE READING

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