Search Results for author: Qihang Yu

Found 20 papers, 11 papers with code

k-means Mask Transformer

1 code implementation8 Jul 2022 Qihang Yu, Huiyu Wang, Siyuan Qiao, Maxwell Collins, Yukun Zhu, Hartwig Adam, Alan Yuille, Liang-Chieh Chen

However, we observe that most existing transformer-based vision models simply borrow the idea from NLP, neglecting the crucial difference between languages and images, particularly the extremely large sequence length of spatially flattened pixel features.

Object Detection Panoptic Segmentation

DeepLab2: A TensorFlow Library for Deep Labeling

1 code implementation17 Jun 2021 Mark Weber, Huiyu Wang, Siyuan Qiao, Jun Xie, Maxwell D. Collins, Yukun Zhu, Liangzhe Yuan, Dahun Kim, Qihang Yu, Daniel Cremers, Laura Leal-Taixe, Alan L. Yuille, Florian Schroff, Hartwig Adam, Liang-Chieh Chen

DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a state-of-the-art and easy-to-use TensorFlow codebase for general dense pixel prediction problems in computer vision.

Glance-and-Gaze Vision Transformer

1 code implementation NeurIPS 2021 Qihang Yu, Yingda Xia, Yutong Bai, Yongyi Lu, Alan Yuille, Wei Shen

It is motivated by the Glance and Gaze behavior of human beings when recognizing objects in natural scenes, with the ability to efficiently model both long-range dependencies and local context.

TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

14 code implementations8 Feb 2021 Jieneng Chen, Yongyi Lu, Qihang Yu, Xiangde Luo, Ehsan Adeli, Yan Wang, Le Lu, Alan L. Yuille, Yuyin Zhou

Medical image segmentation is an essential prerequisite for developing healthcare systems, especially for disease diagnosis and treatment planning.

Cardiac Segmentation Image Segmentation +2

Mask Guided Matting via Progressive Refinement Network

1 code implementation CVPR 2021 Qihang Yu, Jianming Zhang, He Zhang, Yilin Wang, Zhe Lin, Ning Xu, Yutong Bai, Alan Yuille

We propose Mask Guided (MG) Matting, a robust matting framework that takes a general coarse mask as guidance.

Image Matting

Shape-Texture Debiased Neural Network Training

1 code implementation ICLR 2021 Yingwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan Yuille, Cihang Xie

To prevent models from exclusively attending on a single cue in representation learning, we augment training data with images with conflicting shape and texture information (eg, an image of chimpanzee shape but with lemon texture) and, most importantly, provide the corresponding supervisions from shape and texture simultaneously.

Adversarial Robustness Data Augmentation +2

Neural Architecture Search for Lightweight Non-Local Networks

2 code implementations CVPR 2020 Yingwei Li, Xiaojie Jin, Jieru Mei, Xiaochen Lian, Linjie Yang, Cihang Xie, Qihang Yu, Yuyin Zhou, Song Bai, Alan Yuille

However, it has been rarely explored to embed the NL blocks in mobile neural networks, mainly due to the following challenges: 1) NL blocks generally have heavy computation cost which makes it difficult to be applied in applications where computational resources are limited, and 2) it is an open problem to discover an optimal configuration to embed NL blocks into mobile neural networks.

Image Classification Neural Architecture Search

CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks

1 code implementation28 Mar 2020 Qihang Yu, Yingwei Li, Jieru Mei, Yuyin Zhou, Alan L. Yuille

3D Convolution Neural Networks (CNNs) have been widely applied to 3D scene understanding, such as video analysis and volumetric image recognition.

3D Medical Imaging Segmentation Action Recognition +3

When Radiology Report Generation Meets Knowledge Graph

no code implementations19 Feb 2020 Yixiao Zhang, Xiaosong Wang, Ziyue Xu, Qihang Yu, Alan Yuille, Daguang Xu

In addition, we proposed a new evaluation metric for radiology image reporting with the assistance of the same composed graph.

Graph Embedding Image Captioning

C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation

no code implementations CVPR 2020 Qihang Yu, Dong Yang, Holger Roth, Yutong Bai, Yixiao Zhang, Alan L. Yuille, Daguang Xu

3D convolution neural networks (CNN) have been proved very successful in parsing organs or tumours in 3D medical images, but it remains sophisticated and time-consuming to choose or design proper 3D networks given different task contexts.

Image Segmentation Medical Image Segmentation +2

Thickened 2D Networks for Efficient 3D Medical Image Segmentation

no code implementations2 Apr 2019 Qihang Yu, Yingda Xia, Lingxi Xie, Elliot K. Fishman, Alan L. Yuille

With this design, we achieve a higher performance while maintaining a lower inference latency on a few abdominal organs from CT scans, in particular when the organ has a peculiar 3D shape and thus strongly requires contextual information, demonstrating our method's effectiveness and ability in capturing 3D information.

Image Segmentation Medical Image Segmentation +1

Recurrent Saliency Transformation Network: Incorporating Multi-Stage Visual Cues for Small Organ Segmentation

2 code implementations CVPR 2018 Qihang Yu, Lingxi Xie, Yan Wang, Yuyin Zhou, Elliot K. Fishman, Alan L. Yuille

The key innovation is a saliency transformation module, which repeatedly converts the segmentation probability map from the previous iteration as spatial weights and applies these weights to the current iteration.

Organ Segmentation Pancreas Segmentation

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