Search Results for author: Xiaonan Luo

Found 15 papers, 5 papers with code

Gland segmentation via dual encoders and boundary-enhanced attention

no code implementations29 Jan 2024 Huadeng Wang, Jiejiang Yu, Bingbing Li, Xipeng Pan, Zhenbing Liu, Rushi Lan, Xiaonan Luo

Accurate and automated gland segmentation on pathological images can assist pathologists in diagnosing the malignancy of colorectal adenocarcinoma.

Segmentation

A Novel Dataset and a Deep Learning Method for Mitosis Nuclei Segmentation and Classification

no code implementations27 Dec 2022 Huadeng Wang, Zhipeng Liu, Rushi Lan, Zhenbing Liu, Xiaonan Luo, Xipeng Pan, Bingbing Li

In addition, the model also achieves good performance on GZMH dataset, which is prepared by our group and will be firstly released with the publication of this paper.

Segmentation

Binary Representation via Jointly Personalized Sparse Hashing

1 code implementation31 Aug 2022 Xiaoqin Wang, Chen Chen, Rushi Lan, Licheng Liu, Zhenbing Liu, Huiyu Zhou, Xiaonan Luo

Different personalized subspaces are constructed to reflect category-specific attributes for different clusters, adaptively mapping instances within the same cluster to the same Hamming space.

Representation Learning

Neural Points: Point Cloud Representation with Neural Fields for Arbitrary Upsampling

1 code implementation CVPR 2022 Wanquan Feng, Jin Li, Hongrui Cai, Xiaonan Luo, Juyong Zhang

Different from traditional point cloud representation where each point only represents a position or a local plane in the 3D space, each point in Neural Points represents a local continuous geometric shape via neural fields.

GAN for Vision, KG for Relation: a Two-stage Deep Network for Zero-shot Action Recognition

no code implementations25 May 2021 Bin Sun, Dehui Kong, Shaofan Wang, Jinghua Li, BaoCai Yin, Xiaonan Luo

In the sampling stage, we utilize a generative adversarial networks (GAN) trained by action features and word vectors of seen classes to synthesize the action features of unseen classes, which can balance the training sample data of seen classes and unseen classes.

Action Recognition Classification +3

Multi-column Point-CNN for Sketch Segmentation

no code implementations28 Dec 2018 Fei Wang, Shujin Lin, Hanhui Li, Hefeng Wu, Junkun Jiang, Ruomei Wang, Xiaonan Luo

Traditional sketch segmentation methods mainly rely on handcrafted features and complicate models, and their performance is far from satisfactory due to the abstract representation of sketches.

Neural Task Planning with And-Or Graph Representations

no code implementations25 Aug 2018 Tianshui Chen, Riquan Chen, Lin Nie, Xiaonan Luo, Xiaobai Liu, Liang Lin

This paper focuses on semantic task planning, i. e., predicting a sequence of actions toward accomplishing a specific task under a certain scene, which is a new problem in computer vision research.

Common Sense Reasoning valid

Fine-Grained Representation Learning and Recognition by Exploiting Hierarchical Semantic Embedding

1 code implementation14 Aug 2018 Tianshui Chen, Wenxi Wu, Yuefang Gao, Le Dong, Xiaonan Luo, Liang Lin

In this work, we investigate simultaneously predicting categories of different levels in the hierarchy and integrating this structured correlation information into the deep neural network by developing a novel Hierarchical Semantic Embedding (HSE) framework.

Fine-Grained Image Classification Fine-Grained Image Recognition +1

Structured Inhomogeneous Density Map Learning for Crowd Counting

no code implementations20 Jan 2018 Hanhui Li, Xiangjian He, Hefeng Wu, Saeed Amirgholipour Kasmani, Ruomei Wang, Xiaonan Luo, Liang Lin

In this paper, we aim at tackling the problem of crowd counting in extremely high-density scenes, which contain hundreds, or even thousands of people.

Crowd Counting

Learning Deep Similarity Models with Focus Ranking for Fabric Image Retrieval

no code implementations29 Dec 2017 Daiguo Deng, Ruomei Wang, Hefeng Wu, Huayong He, Qi Li, Xiaonan Luo

Fabric image retrieval is beneficial to many applications including clothing searching, online shopping and cloth modeling.

Image Retrieval Representation Learning +1

Learning a Wavelet-like Auto-Encoder to Accelerate Deep Neural Networks

2 code implementations20 Dec 2017 Tianshui Chen, Liang Lin, WangMeng Zuo, Xiaonan Luo, Lei Zhang

In this work, aiming at a general and comprehensive way for neural network acceleration, we develop a Wavelet-like Auto-Encoder (WAE) that decomposes the original input image into two low-resolution channels (sub-images) and incorporate the WAE into the classification neural networks for joint training.

Classification General Classification +1

Learning to Segment Object Candidates via Recursive Neural Networks

no code implementations4 Dec 2016 Tianshui Chen, Liang Lin, Xian Wu, Nong Xiao, Xiaonan Luo

To avoid the exhaustive search over locations and scales, current state-of-the-art object detection systems usually involve a crucial component generating a batch of candidate object proposals from images.

Object object-detection +1

DISC: Deep Image Saliency Computing via Progressive Representation Learning

no code implementations13 Nov 2015 Tianshui Chen, Liang Lin, Lingbo Liu, Xiaonan Luo, Xuelong. Li

Our DISC framework is capable of uniformly highlighting the objects-of-interest from complex background while preserving well object details.

object-detection Representation Learning +2

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