Search Results for author: Changming Sun

Found 18 papers, 7 papers with code

Instance-Aware Embedding for Point Cloud Instance Segmentation

no code implementations ECCV 2020 Tong He, Yifan Liu, Chunhua Shen, Xinlong Wang, Changming Sun

However, these methods are unaware of the instance context and fail to realize the boundary and geometric information of an instance, which are critical to separate adjacent objects.

Instance Segmentation Semantic Segmentation

ReDro: Efficiently Learning Large-sized SPD Visual Representation

no code implementations ECCV 2020 Saimunur Rahman, Lei Wang, Changming Sun, Luping Zhou

When learning this representation in deep networks, eigen-decomposition of covariance matrix is usually needed for a key step called matrix normalisation.

Fine-Grained Image Classification

Calibrating a Deep Neural Network with Its Predecessors

no code implementations13 Feb 2023 Linwei Tao, Minjing Dong, Daochang Liu, Changming Sun, Chang Xu

However, early stopping, as a well-known technique to mitigate overfitting, fails to calibrate networks.

EOCSA: Predicting Prognosis of Epithelial Ovarian Cancer with Whole Slide Histopathological Images

1 code implementation11 Oct 2022 Tianling Liu, Ran Su, Changming Sun, Xiuting Li, Leyi Wei

Next, we developed a survival prediction model, named DeepConvAttentionSurv (DCAS), which was able to extract patch-level features, removed less discriminative clusters and predicted the EOC survival precisely.

Survival Analysis Survival Prediction +1

Improving Monocular Visual Odometry Using Learned Depth

no code implementations4 Apr 2022 Libo Sun, Wei Yin, Enze Xie, Zhengrong Li, Changming Sun, Chunhua Shen

The core of our framework is a monocular depth estimation module with a strong generalization capability for diverse scenes.

Monocular Depth Estimation Monocular Visual Odometry

Image Feature Information Extraction for Interest Point Detection: A Review

no code implementations15 Jun 2021 Junfeng Jing, Tian Gao, Weichuan Zhang, Yongsheng Gao, Changming Sun

The existing popular datasets and evaluation standards are provided and the performances for eighteen state-of-the-art approaches are evaluated and discussed.

Interest Point Detection

NDPNet: A novel non-linear data projection network for few-shot fine-grained image classification

no code implementations13 Jun 2021 Weichuan Zhang, Xuefang Liu, Zhe Xue, Yongsheng Gao, Changming Sun

Metric-based few-shot fine-grained image classification (FSFGIC) aims to learn a transferable feature embedding network by estimating the similarities between query images and support classes from very few examples.

Few-Shot Learning Fine-Grained Image Classification +1

Domain adaptation based self-correction model for COVID-19 infection segmentation in CT images

1 code implementation20 Apr 2021 Qiangguo Jin, Hui Cui, Changming Sun, Zhaopeng Meng, Leyi Wei, Ran Su

DASC-Net consists of a novel attention and feature domain enhanced domain adaptation model (AFD-DA) to solve the domain shifts and a self-correction learning process to refine segmentation results.

Domain Adaptation

Free-form tumor synthesis in computed tomography images via richer generative adversarial network

1 code implementation20 Apr 2021 Qiangguo Jin, Hui Cui, Changming Sun, Zhaopeng Meng, Ran Su

The network is composed of a new richer convolutional feature enhanced dilated-gated generator (RicherDG) and a hybrid loss function.

Association Computed Tomography (CT)

A Robust Matching Pursuit Algorithm Using Information Theoretic Learning

no code implementations10 May 2020 Miaohua Zhang, Yongsheng Gao, Changming Sun, Michael Blumenstein

Current orthogonal matching pursuit (OMP) algorithms calculate the correlation between two vectors using the inner product operation and minimize the mean square error, which are both suboptimal when there are non-Gaussian noises or outliers in the observation data.

Image Reconstruction

Robust Tensor Decomposition for Image Representation Based on Generalized Correntropy

no code implementations10 May 2020 Miaohua Zhang, Yongsheng Gao, Changming Sun, Michael Blumenstein

Traditional tensor decomposition methods, e. g., two dimensional principal component analysis and two dimensional singular value decomposition, that minimize mean square errors, are sensitive to outliers.

Face Reconstruction Handwritten Digit Recognition +2

DiverseDepth: Affine-invariant Depth Prediction Using Diverse Data

2 code implementations3 Feb 2020 Wei Yin, Xinlong Wang, Chunhua Shen, Yifan Liu, Zhi Tian, Songcen Xu, Changming Sun, Dou Renyin

Compared with previous learning objectives, i. e., learning metric depth or relative depth, we propose to learn the affine-invariant depth using our diverse dataset to ensure both generalization and high-quality geometric shapes of scenes.

Depth Estimation Depth Prediction

Deep Learning based HEp-2 Image Classification: A Comprehensive Review

no code implementations20 Nov 2019 Saimunur Rahman, Lei Wang, Changming Sun, Luping Zhou

This paper provides a comprehensive review of the existing deep learning based HEp-2 cell image classification methods.

Classification General Classification +1

Knowledge Adaptation for Efficient Semantic Segmentation

1 code implementation CVPR 2019 Tong He, Chunhua Shen, Zhi Tian, Dong Gong, Changming Sun, Youliang Yan

To tackle this dilemma, we propose a knowledge distillation method tailored for semantic segmentation to improve the performance of the compact FCNs with large overall stride.

Knowledge Distillation Semantic Segmentation

RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scans

1 code implementation4 Nov 2018 Qiangguo Jin, Zhaopeng Meng, Changming Sun, Leyi Wei, Ran Su

Automatic extraction of liver and tumor from CT volumes is a challenging task due to their heterogeneous and diffusive shapes.

Brain Tumor Segmentation Deep Attention +2

An end-to-end TextSpotter with Explicit Alignment and Attention

2 code implementations CVPR 2018 Tong He, Zhi Tian, Weilin Huang, Chunhua Shen, Yu Qiao, Changming Sun

This allows the two tasks to work collaboratively by shar- ing convolutional features, which is critical to identify challenging text instances.

Can Walking and Measuring Along Chord Bunches Better Describe Leaf Shapes?

no code implementations CVPR 2017 Bin Wang, Yongsheng Gao, Changming Sun, Michael Blumenstein, John La Salle

A novel chord bunch walks (CBW) descriptor is developed through the chord walking that effectively integrates the shape image function over the walked chord to reflect the contour features and the inner properties of the shape.


Multipoint Filtering with Local Polynomial Approximation and Range Guidance

no code implementations CVPR 2014 Xiao Tan, Changming Sun, Tuan D. Pham

By using the hybrid of the local polynomial model and color/intensity based range guidance, the proposed method not only preserves edges but also does a much better job in preserving spatial variation than existing popular filtering methods.

Depth Image Upsampling Image Denoising

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