Search Results for author: Kongming Liang

Found 18 papers, 10 papers with code

Vision-language Assisted Attribute Learning

no code implementations12 Dec 2023 Kongming Liang, Xinran Wang, Rui Wang, Donghui Gao, Ling Jin, Weidong Liu, Xiatian Zhu, Zhanyu Ma, Jun Guo

Attribute labeling at large scale is typically incomplete and partial, posing significant challenges to model optimization.

Attribute Language Modelling +1

Ariadne's Thread:Using Text Prompts to Improve Segmentation of Infected Areas from Chest X-ray images

1 code implementation8 Jul 2023 Yi Zhong, Mengqiu Xu, Kongming Liang, Kaixin Chen, Ming Wu

Segmentation of the infected areas of the lung is essential for quantifying the severity of lung disease like pulmonary infections.

Image Segmentation Medical Image Segmentation +2

Super-Resolution Information Enhancement For Crowd Counting

1 code implementation13 Mar 2023 Jiahao Xie, Wei Xu, Dingkang Liang, Zhanyu Ma, Kongming Liang, Weidong Liu, Rui Wang, Ling Jin

As the proposed method requires SR labels, we further propose a Super-Resolution Crowd Counting dataset (SR-Crowd).

Crowd Counting Super-Resolution

Graph Convolution Based Cross-Network Multi-Scale Feature Fusion for Deep Vessel Segmentation

no code implementations6 Jan 2023 Gangming Zhao, Kongming Liang, Chengwei Pan, Fandong Zhang, Xianpeng Wu, Xinyang Hu, Yizhou Yu

To tackle the challenges caused by the sparsity and anisotropy of vessels, a higher percentage of graph nodes are distributed in areas that potentially contain vessels while a higher percentage of edges follow the orientation of potential nearbyvessels.


Multi-head Uncertainty Inference for Adversarial Attack Detection

no code implementations20 Dec 2022 YuQi Yang, Songyun Yang, Jiyang Xie. Zhongwei Si, Kai Guo, Ke Zhang, Kongming Liang

We adopt a multi-head architecture with multiple prediction heads (i. e., classifiers) to obtain predictions from different depths in the DNNs and introduce shallow information for the UI.

Adversarial Attack Detection Adversarial Defense

Learning Invariant Visual Representations for Compositional Zero-Shot Learning

1 code implementation1 Jun 2022 Tian Zhang, Kongming Liang, Ruoyi Du, Xian Sun, Zhanyu Ma, Jun Guo

Compositional Zero-Shot Learning (CZSL) aims to recognize novel compositions using knowledge learned from seen attribute-object compositions in the training set.

Attribute Compositional Zero-Shot Learning +2

Domain Generalization via Frequency-domain-based Feature Disentanglement and Interaction

no code implementations20 Jan 2022 Jingye Wang, Ruoyi Du, Dongliang Chang, Kongming Liang, Zhanyu Ma

Adaptation to out-of-distribution data is a meta-challenge for all statistical learning algorithms that strongly rely on the i. i. d.

Data Augmentation Disentanglement +2

Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non-Contrast CT Images

1 code implementation11 Oct 2021 Kongming Liang, Kai Han, Xiuli Li, Xiaoqing Cheng, Yiming Li, Yizhou Wang, Yizhou Yu

In this paper, we propose a symmetry enhanced attention network (SEAN) for acute ischemic infarct segmentation.

Cross-layer Navigation Convolutional Neural Network for Fine-grained Visual Classification

no code implementations21 Jun 2021 Chenyu Guo, Jiyang Xie, Kongming Liang, Xian Sun, Zhanyu Ma

Then, attention mechanisms are used after feature fusion to extract spatial and channel information while linking the high-level semantic information and the low-level texture features, which can better locate the discriminative regions for the FGVC.

Fine-Grained Image Classification

DF^2AM: Dual-level Feature Fusion and Affinity Modeling for RGB-Infrared Cross-modality Person Re-identification

no code implementations1 Apr 2021 Junhui Yin, Zhanyu Ma, Jiyang Xie, Shibo Nie, Kongming Liang, Jun Guo

Meanwhile, to further mining the relationships between global features from person images, we propose an Affinities Modeling (AM) module to obtain the optimal intra- and inter-modality image matching.

Cross-Modality Person Re-identification Person Re-Identification

Duplex Contextual Relation Network for Polyp Segmentation

1 code implementation11 Mar 2021 Zijin Yin, Kongming Liang, Zhanyu Ma, Jun Guo

However, previous methods only focus on learning the dependencies between the position within an individual image and ignore the contextual relation across different images.

Position Relation +1

Fine-Grained Visual Classification via Simultaneously Learning of Multi-regional Multi-grained Features

2 code implementations31 Jan 2021 Dongliang Chang, Yixiao Zheng, Zhanyu Ma, Ruoyi Du, Kongming Liang

Finally, we can obtain multiple discriminative regions on high-level feature channels and obtain multiple more minute regions within these discriminative regions on middle-level feature channels.

Fine-Grained Image Classification General Classification

Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation

1 code implementation10 Jul 2020 Shen Wang, Kongming Liang, Yiming Li, Yizhou Yu, Yizhou Wang

Nevertheless, there are still great challenges with brain midline delineation, such as the largely deformed midline caused by the mass effect and the possible morphological failure that the predicted midline is not a connected curve.

Segmentation-based Method combined with Dynamic Programming for Brain Midline Delineation

no code implementations27 Feb 2020 Shen Wang, Kongming Liang, Chengwei Pan, Chuyang Ye, Xiuli Li, Feng Liu, Yizhou Yu, Yizhou Wang

The midline related pathological image features are crucial for evaluating the severity of brain compression caused by stroke or traumatic brain injury (TBI).

Decision Making

FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation

12 code implementations28 Mar 2019 Huikai Wu, Junge Zhang, Kaiqi Huang, Kongming Liang, Yizhou Yu

Modern approaches for semantic segmentation usually employ dilated convolutions in the backbone to extract high-resolution feature maps, which brings heavy computation complexity and memory footprint.

Semantic Segmentation

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