8 code implementations • ECCV 2018 • Sachin Mehta, Mohammad Rastegari, Anat Caspi, Linda Shapiro, Hannaneh Hajishirzi
We introduce a fast and efficient convolutional neural network, ESPNet, for semantic segmentation of high resolution images under resource constraints.
Ranked #48 on Semantic Segmentation on PASCAL VOC 2012 test
9 code implementations • CVPR 2019 • Sachin Mehta, Mohammad Rastegari, Linda Shapiro, Hannaneh Hajishirzi
Compared to YOLOv2 on the MS-COCO object detection, ESPNetv2 delivers 4. 4% higher accuracy with 6x fewer FLOPs.
Ranked #41 on Semantic Segmentation on PASCAL VOC 2012 test
2 code implementations • 4 Jun 2018 • Sachin Mehta, Ezgi Mercan, Jamen Bartlett, Donald Weave, Joann G. Elmore, Linda Shapiro
In this paper, we introduce a conceptually simple network for generating discriminative tissue-level segmentation masks for the purpose of breast cancer diagnosis.
1 code implementation • 7 Dec 2023 • Mehmet Saygin Seyfioglu, Wisdom O. Ikezogwo, Fatemeh Ghezloo, Ranjay Krishna, Linda Shapiro
Training multi-model models for histopathology requires instruction tuning datasets, which currently contain information for individual image patches, without a spatial grounding of the concepts within each patch and without a wider view of the WSI.
1 code implementation • NeurIPS 2023 • Wisdom Oluchi Ikezogwo, Mehmet Saygin Seyfioglu, Fatemeh Ghezloo, Dylan Stefan Chan Geva, Fatwir Sheikh Mohammed, Pavan Kumar Anand, Ranjay Krishna, Linda Shapiro
From YouTube, we curate QUILT: a large-scale vision-language dataset consisting of $802, 144$ image and text pairs.
1 code implementation • 25 Jul 2020 • Sachin Mehta, Ximing Lu, Donald Weaver, Joann G. Elmore, Hannaneh Hajishirzi, Linda Shapiro
HATNet extends the bag-of-words approach and uses self-attention to encode global information, allowing it to learn representations from clinically relevant tissue structures without any explicit supervision.
1 code implementation • 8 Sep 2017 • Sachin Mehta, Ezgi Mercan, Jamen Bartlett, Donald Weaver, Joann Elmore, Linda Shapiro
We trained and applied an encoder-decoder model to semantically segment breast biopsy images into biologically meaningful tissue labels.
1 code implementation • 4 Sep 2022 • Wisdom Oluchi Ikezogwo, Mehmet Saygin Seyfioglu, Linda Shapiro
However, the domain shift between natural images and digital pathology images requires further research in designing MAE for patch-level WSIs.
1 code implementation • 11 Aug 2021 • Beibin Li, Nicholas Nuechterlein, Erin Barney, Claire Foster, Minah Kim, Monique Mahony, Adham Atyabi, Li Feng, Quan Wang, Pamela Ventola, Linda Shapiro, Frederick Shic
Identifying oculomotor behaviors relevant for eye-tracking applications is a critical but often challenging task.
1 code implementation • 11 Jul 2022 • Mehmet Saygın Seyfioğlu, Zixuan Liu, Pranav Kamath, Sadjyot Gangolli, Sheng Wang, Thomas Grabowski, Linda Shapiro
On top of BAR, we propose using a soft-label-capable supervised contrastive loss, aiming to learn the relative similarity of representations that reflect how mixed are the synthetic MRIs using our soft labels.
no code implementations • 21 Nov 2017 • Sachin Mehta, Hannaneh Hajishirzi, Linda Shapiro
We present an approach for identifying the most walkable direction for navigation using a hand-held camera.
no code implementations • CVPR 2013 • Shulin Yang, Jue Wang, Linda Shapiro
This paper proposes a new supervised semantic edge and gradient extraction approach, which allows the user to roughly scribble over the desired region to extract semantically-dominant and coherent edges in it.
no code implementations • CVPR 2016 • Yao Lu, Xue Bai, Linda Shapiro, Jue Wang
Interactive video segmentation systems aim at producing sub-pixel-level object boundaries for visual effect applications.
no code implementations • ICCV 2015 • Bilge Soran, Ali Farhadi, Linda Shapiro
The overall prediction accuracy is 46. 2% when only 10 frames of an action are seen (2/3 of a sec).
no code implementations • 7 Apr 2019 • Beibin Li, Sachin Mehta, Deepali Aneja, Claire Foster, Pamela Ventola, Frederick Shic, Linda Shapiro
In this paper, we introduce an end-to-end machine learning-based system for classifying autism spectrum disorder (ASD) using facial attributes such as expressions, action units, arousal, and valence.
no code implementations • 19 Nov 2019 • Deepali Aneja, Alex Colburn, Gary Faigin, Linda Shapiro, Barbara Mones
We present DeepExpr, a novel expression transfer system from humans to multiple stylized characters via deep learning.
1 code implementation • 29 Nov 2019 • Beibin Li, Nicholas Nuechterlein, Erin Barney, Caitlin Hudac, Pamela Ventola, Linda Shapiro, Frederick Shic
In genomic analysis, biomarker discovery, image recognition, and other systems involving machine learning, input variables can often be organized into different groups by their source or semantic category.
no code implementations • ECCV 2020 • Bindita Chaudhuri, Noranart Vesdapunt, Linda Shapiro, Baoyuan Wang
Traditional methods for image-based 3D face reconstruction and facial motion retargeting fit a 3D morphable model (3DMM) to the face, which has limited modeling capacity and fail to generalize well to in-the-wild data.
no code implementations • CVPR 2021 • Bindita Chaudhuri, Nikolaos Sarafianos, Linda Shapiro, Tony Tung
Given a segmentation mask defining the layout of the semantic regions in the texture map, our network generates high-resolution textures with a variety of styles, that are then used for rendering purposes.
no code implementations • 4 Jan 2024 • Xinzhe Luo, Xin Wang, Linda Shapiro, Chun Yuan, Jianfeng Feng, Xiahai Zhuang
This article presents a general Bayesian learning framework for multi-modal groupwise registration on medical images.