Search Results for author: Linda G. Shapiro

Found 5 papers, 1 papers with code

Classifying Breast Histopathology Images with a Ductal Instance-Oriented Pipeline

1 code implementation11 Dec 2020 Beibin Li, Ezgi Mercan, Sachin Mehta, Stevan Knezevich, Corey W. Arnold, Donald L. Weaver, Joann G. Elmore, Linda G. Shapiro

In this study, we propose the Ductal Instance-Oriented Pipeline (DIOP) that contains a duct-level instance segmentation model, a tissue-level semantic segmentation model, and three-levels of features for diagnostic classification.

General Classification Instance Segmentation +1

3D Face Hallucination from a Single Depth Frame

no code implementations13 Sep 2018 Shu Liang, Ira Kemelmacher-Shlizerman, Linda G. Shapiro

We further combine the input depth frame with the matched database shapes into a single mesh that results in a high-resolution shape of the input person.

Face Hallucination

Head Reconstruction from Internet Photos

no code implementations13 Sep 2018 Shu Liang, Linda G. Shapiro, Ira Kemelmacher-Shlizerman

Our method is to gradually "grow" the head mesh starting from the frontal face and extending to the rest of views using photometric stereo constraints.

3D Face Reconstruction

Video to Fully Automatic 3D Hair Model

no code implementations13 Sep 2018 Shu Liang, Xiufeng Huang, Xianyu Meng, Kunyao Chen, Linda G. Shapiro, Ira Kemelmacher-Shlizerman

In this paper, we describe a system that can completely automatically create a reconstruction from any video (even a selfie video), and we don't require specific views, since taking your -90 degree, 90 degree, and full back views is not feasible in a selfie capture.

Unsupervised Template Learning for Fine-Grained Object Recognition

no code implementations NeurIPS 2012 Shulin Yang, Liefeng Bo, Jue Wang, Linda G. Shapiro

It differs from recognition of basic categories, such as humans, tables, and computers, in that there are global similarities in shape or structure shared within a category, and the differences are in the details of the object parts.

Object Recognition

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