1 code implementation • 2 Mar 2024 • Zijin Yin, Kongming Liang, Bing Li, Zhanyu Ma, Jun Guo
We evaluate a broad variety of semantic segmentation models, spanning from conventional close-set models to recent open-vocabulary large models on their robustness to different types of variations.
no code implementations • 12 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.
1 code implementation • 8 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.
1 code implementation • 13 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).
no code implementations • 6 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.
1 code implementation • CVPR 2023 • Ruoyi Du, Dongliang Chang, Kongming Liang, Timothy Hospedales, Yi-Zhe Song, Zhanyu Ma
Our code is available at https://github. com/PRIS-CV/On-the-fly-Category-Discovery.
no code implementations • 20 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.
1 code implementation • 1 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.
no code implementations • 20 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.
1 code implementation • 11 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.
no code implementations • 21 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.
no code implementations • 1 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
1 code implementation • 11 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.
2 code implementations • 31 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.
1 code implementation • 10 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.
no code implementations • 27 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).
12 code implementations • 28 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.
Ranked #40 on Semantic Segmentation on PASCAL Context
1 code implementation • 27 Apr 2018 • Kongming Liang, Yuhong Guo, Hong Chang, Xilin Chen
In this paper, we propose a novel framework, called Deep Structural Ranking, for visual relationship detection.
no code implementations • ICCV 2015 • Kongming Liang, Hong Chang, Shiguang Shan, Xilin Chen
Attributes are mid-level semantic properties of objects.