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Taobao Commodity Dataset

Taobao Commodity Dataset

Scene:

Fashion,Common

Data Type:

Classification
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中山大学人机物智能融合实验室

Our laboratory seeks general and task-driven ways to build intelligence, embracing the access to the ternary human-cyber-physical universe.

Data Preview ? 30.5M

    Data Structure ?

    *数据结构实际以真实数据为准

    TCD contains 800 commodity images (dresses, jeans, T-shirts, shoes and hats) from the shops on the Taobao website. The ground truth masks of the TCD dataset are obtained by inviting common sellers of Taobao website to annotate their commodities, i.e., masking salient objects that they want to show from their exhibition. These images include all kinds of commodity with and without human models, thus having complex backgrounds and scenes with highly complex foregrounds. Pixel-accurate ground truth masks are given. These images including all kinds of commodities with and without human models have complex backgrounds and scenes with large foregrounds for evaluation. Figure 1 illustrates some of them.

    evaluation

    We evaluate several state-of-the-art saliency detection methods DSR[1], GC[2], HS[3], SF[4], RC[5], HC[5], CA[6], FT[7], SR[8] and LC[9] on this dataset. The precision-recall curve and F-measure curves are plotted in the following figures left and right.

    Results of the state-of-art methods


    PR

    FMeasure


    References

    DSR [1] X. Li, H. Lu, L. Zhang, X. Ruan, and M.H. Yang. “Saliency Detection via Dense and Sparse Reconstruction,” in IEEE ICCV, 2013.
    GC [2] M.M. Cheng, J. Warrell, W.Y. Lin, S. Zheng, V. Vineet, and N. Crook. “Efficient Salient Region Detection with Soft Image Abstraction,” in IEEE ICCV, 2013.
    HS [3] Q. Yan, L. Xu, J. Shi, and J. Jia. “Hierarchical Saliency Detection,” in IEEE CVPR, 2013, pp. 1155–1162.
    SF [4] F. Perazzi, P. Krahenbuhl, Y. Pritch, and A. Hornung. “Saliency filters: contrast based filtering for salient region detection,” in CVPR, 2012, pp. 733–740.
    HC,RC [5] M. Cheng, G. Zhang, N. Mitra, X. Huang, and S. Hu. “Global contrast based salient region detection,” in CVPR, 2011.
    CA [6] S. Goferman, L. Zelnik-Manor, and A. Tal, “Context-aware saliency detection,” in IEEE CVPR, 2010, pp. 2376–2383.
    FT [7] R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk.“Frequency-tuned salient region detection,” in IEEE CVPR, 2009, pp. 1597–1604.
    SR [8] X. Hou, and L. Zhang. “Saliency detection: A spectral residual approach,” in IEEE CVPR, 2007, pp. 1–8.
    LC [9] Y. Zhai and M. Shah, “Visual attention detection in video sequences using spatiotemporal cues,” in ACM Multimedia, 2006, pp. 815–824.

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