Search Results for author: Huimin Lu

Found 23 papers, 5 papers with code

Thunder: Thumbnail based Fast Lightweight Image Denoising Network

no code implementations24 May 2022 Yifeng Zhou, Xing Xu, Shuaicheng Liu, Guoqing Wang, Huimin Lu, Heng Tao Shen

To achieve promising results on removing noise from real-world images, most of existing denoising networks are formulated with complex network structure, making them impractical for deployment.

Image Denoising SSIM

Feature Distillation Interaction Weighting Network for Lightweight Image Super-Resolution

1 code implementation16 Dec 2021 Guangwei Gao, Wenjie Li, Juncheng Li, Fei Wu, Huimin Lu, Yi Yu

Convolutional neural networks based single-image super-resolution (SISR) has made great progress in recent years.

Image Super-Resolution

FBSNet: A Fast Bilateral Symmetrical Network for Real-Time Semantic Segmentation

1 code implementation2 Sep 2021 Guangwei Gao, Guoan Xu, Juncheng Li, Yi Yu, Huimin Lu, Jian Yang

Specifically, FBSNet employs a symmetrical encoder-decoder structure with two branches, semantic information branch and spatial detail branch.

Autonomous Driving Drone navigation +1

Partial Feature Selection and Alignment for Multi-Source Domain Adaptation

no code implementations CVPR 2021 Yangye Fu, Ming Zhang, Xing Xu, Zuo Cao, Chao Ma, Yanli Ji, Kai Zuo, Huimin Lu

By assuming that the source and target domains share consistent key feature representations and identical label space, existing studies on MSDA typically utilize the entire union set of features from both the source and target domains to obtain the feature map and align the map for each category and domain.

feature selection Partial Domain Adaptation

JDSR-GAN: Constructing A Joint and Collaborative Learning Network for Masked Face Super-Resolution

no code implementations25 Mar 2021 Guangwei Gao, Lei Tang, Yi Yu, Fei Wu, Huimin Lu, Jian Yang

In this work, we treat the mask occlusion as image noise and construct a joint and collaborative learning network, called JDSR-GAN, for the masked face super-resolution task.

Denoising Super-Resolution

Lightweight Image Super-Resolution with Multi-scale Feature Interaction Network

no code implementations24 Mar 2021 Zhengxue Wang, Guangwei Gao, Juncheng Li, Yi Yu, Huimin Lu

Recently, the single image super-resolution (SISR) approaches with deep and complex convolutional neural network structures have achieved promising performance.

Image Super-Resolution

3DMNDT:3D multi-view registration method based on the normal distributions transform

no code implementations20 Mar 2021 Jihua Zhu, Di Wang, Jiaxi Mu, Huimin Lu, Zhiqiang Tian, Zhongyu Li

Under the NDT framework, this paper proposes a novel multi-view registration method, named 3D multi-view registration based on the normal distributions transform (3DMNDT), which integrates the K-means clustering and Lie algebra solver to achieve multi-view registration.

ORD: Object Relationship Discovery for Visual Dialogue Generation

no code implementations15 Jun 2020 Ziwei Wang, Zi Huang, Yadan Luo, Huimin Lu

With the rapid advancement of image captioning and visual question answering at single-round level, the question of how to generate multi-round dialogue about visual content has not yet been well explored. Existing visual dialogue methods encode the image into a fixed feature vector directly, concatenated with the question and history embeddings to predict the response. Some recent methods tackle the co-reference resolution problem using co-attention mechanism to cross-refer relevant elements from the image, history, and the target question. However, it remains challenging to reason visual relationships, since the fine-grained object-level information is omitted before co-attentive reasoning.

Dialogue Generation Graph Attention +4

Robust Motion Averaging under Maximum Correntropy Criterion

no code implementations21 Apr 2020 Jihua Zhu, Jie Hu, Huimin Lu, Badong Chen, Zhongyu Li

Recently, the motion averaging method has been introduced as an effective means to solve the multi-view registration problem.

Generalized Label Enhancement with Sample Correlations

no code implementations7 Apr 2020 Qinghai Zheng, Jihua Zhu, Haoyu Tang, Xinyuan Liu, Zhongyu Li, Huimin Lu

Recently, label distribution learning (LDL) has drawn much attention in machine learning, where LDL model is learned from labelel instances.

Synergic Adversarial Label Learning for Grading Retinal Diseases via Knowledge Distillation and Multi-task Learning

no code implementations24 Mar 2020 Lie Ju, Xin Wang, Xin Zhao, Huimin Lu, Dwarikanath Mahapatra, Paul Bonnington, ZongYuan Ge

In addition, we conduct additional experiments to show the effectiveness of SALL from the aspects of reliability and interpretability in the context of medical imaging application.

Classification General Classification +2

BiCANet: Bi-directional Contextual Aggregating Network for Image Semantic Segmentation

1 code implementation21 Mar 2020 Quan Zhou, Dechun Cong, Bin Kang, Xiaofu Wu, Baoyu Zheng, Huimin Lu, Longin Jan Latecki

Exploring contextual information in convolution neural networks (CNNs) has gained substantial attention in recent years for semantic segmentation.

Semantic Segmentation

Registration of multi-view point sets under the perspective of expectation-maximization

1 code implementation18 Feb 2020 Jihua Zhu, Jing Zhang, Huimin Lu, Zhongyu Li

Registration of multi-view point sets is a prerequisite for 3D model reconstruction.

Snap and Find: Deep Discrete Cross-domain Garment Image Retrieval

no code implementations5 Apr 2019 Yadan Luo, Ziwei Wang, Zi Huang, Yang Yang, Huimin Lu

With the increasing number of online stores, there is a pressing need for intelligent search systems to understand the item photos snapped by customers and search against large-scale product databases to find their desired items.

Image Retrieval

CONet: A Cognitive Ocean Network

no code implementations9 Jan 2019 Huimin Lu, Dong Wang, Yujie Li, Jianru Li, Xin Li, Hyoungseop Kim, Seiichi Serikawa, Iztok Humar

The Cognitive Ocean Network (CONet) will become the mainstream of future ocean science and engineering developments.

Multi-level Chaotic Maps for 3D Textured Model Encryption

no code implementations25 Sep 2017 Xin Jin, Shuyun Zhu, Le Wu, Geng Zhao, Xiao-Dong Li, Quan Zhou, Huimin Lu

In this work, a multi-level chaotic maps models for 3D textured encryption was presented by observing the different contributions for recognizing cipher 3D models between vertices (point cloud), polygons and textures.

Simultaneous merging multiple grid maps using the robust motion averaging

no code implementations14 Jun 2017 Zutao Jiang, Jihua Zhu, Yaochen Li, Zhongyu Li, Huimin Lu

The main idea of this approach is to recover all global motions for map merging from a set of relative motions.

Brain Intelligence: Go Beyond Artificial Intelligence

no code implementations4 Jun 2017 Huimin Lu, Yujie Li, Min Chen, Hyoungseop Kim, Seiichi Serikawa

Specifically, we plan to develop an intelligent learning model called Brain Intelligence (BI) that generates new ideas about events without having experienced them by using artificial life with an imagine function.

Artificial Life Industrial Robots

An Effective Approach for Point Clouds Registration Based on the Hard and Soft Assignments

no code implementations1 Jun 2017 Congcong Jin, Jihua Zhu, Yaochen Li, Shaoyi Du, Zhongyu Li, Huimin Lu

For the registration of partially overlapping point clouds, this paper proposes an effective approach based on both the hard and soft assignments.

Effective scaling registration approach by imposing the emphasis on the scale factor

no code implementations28 Apr 2017 Minmin Xu, Siyu Xu, Jihua Zhu, Yaochen Li, Jun Wang, Huimin Lu

This paper proposes an effective approach for the scaling registration of $m$-D point sets.

Underwater Optical Image Processing: A Comprehensive Review

no code implementations13 Feb 2017 Huimin Lu, Yujie Li, Yudong Zhang, Min Chen, Seiichi Serikawa, Hyoungseop Kim

This paper aims to review the state-of-the-art techniques in underwater image processing by highlighting the contributions and challenges presented in over 40 papers.

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