Search Results for author: Linda G. Shapiro

Found 7 papers, 2 papers with code

Semantics-Aware Attention Guidance for Diagnosing Whole Slide Images

no code implementations16 Apr 2024 Kechun Liu, Wenjun Wu, Joann G. Elmore, Linda G. Shapiro

Accurate cancer diagnosis remains a critical challenge in digital pathology, largely due to the gigapixel size and complex spatial relationships present in whole slide images.

Anatomy Multiple Instance Learning +1

MIMIC: Masked Image Modeling with Image Correspondences

1 code implementation27 Jun 2023 Kalyani Marathe, Mahtab Bigverdi, Nishat Khan, Tuhin Kundu, Patrick Howe, Sharan Ranjit S, Anand Bhattad, Aniruddha Kembhavi, Linda G. Shapiro, Ranjay Krishna

We train multiple models with different masked image modeling objectives to showcase the following findings: Representations trained on our automatically generated MIMIC-3M outperform those learned from expensive crowdsourced datasets (ImageNet-1K) and those learned from synthetic environments (MULTIVIEW-HABITAT) on two dense geometric tasks: depth estimation on NYUv2 (1. 7%), and surface normals estimation on Taskonomy (2. 05%).

Depth Estimation Pose Estimation +3

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 +2

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 Hallucination

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.

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

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 Object Recognition

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