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Chapter and Conference Paper
Multi-scale Inter-frame Information Fusion Based Network for Cardiac MRI Reconstruction
Accelerated cine MRI reconstruction from under-sampled data is paramount in clinical diagnosis. Nonetheless, the existing method falls short in fully harnessing inter-frame information, thereby impeding its ov...
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Chapter and Conference Paper
Illumination-Guided Transformer-Based Network for Multispectral Pedestrian Detection
Multi-modal information (e.g., visible and thermal) can generate reliable and robust pedestrian detection results in various computer vision applications. Despite its broad applications, it remains a crucial p...
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Chapter and Conference Paper
Count- and Similarity-Aware R-CNN for Pedestrian Detection
Recent pedestrian detection methods generally rely on additional supervision, such as visible bounding-box annotations, to handle heavy occlusions. We propose an approach that leverages pedestrian count and pr...
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Chapter and Conference Paper
SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation
Single-stage instance segmentation approaches have recently gained popularity due to their speed and simplicity, but are still lagging behind in accuracy, compared to two-stage methods. We propose a fast singl...
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Chapter and Conference Paper
Consensus-Aware Visual-Semantic Embedding for Image-Text Matching
Image-text matching plays a central role in bridging vision and language. Most existing approaches only rely on the image-text instance pair to learn their representations, thereby exploiting their matching re...
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Chapter and Conference Paper
ET-Net: A Generic Edge-aTtention Guidance Network for Medical Image Segmentation
Segmentation is a fundamental task in medical image analysis. However, most existing methods focus on primary region extraction and ignore edge information, which is useful for obtaining accurate segmentation....
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Chapter
Deep Learning in Object Detection
Object detection is an important research area in image processing and computer vision. The performance of object detection has significantly improved through applying deep learning technology. Among these met...
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Chapter and Conference Paper
Cross-Modal Retrieval with Discriminative Dual-Path CNN
Cross-modal retrieval aims at searching semantically similar examples in one modality by using a query from another modality. Its typical applications including image-based text retrieval (IBTR) and text-based...
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Chapter and Conference Paper
Zero-Shot Learning with Deep Canonical Correlation Analysis
Zero-shot learning (ZSL) improves the scalability of conventional image classification systems by allowing some testing categories having no training data. One key component is to learn a shared embedding spac...
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Chapter and Conference Paper
ECG Waveform Extraction from Paper Records
Electrocardiogram (ECG) is one of the most practiced methods to detect any abnormalities in human heart function. ECG waveforms are usually recorded as paper form. However, ECG paper records are inconvenient f...
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Chapter and Conference Paper
Enhancement for Dust-Sand Storm Images
A novel dust-sand storm image enhancement scheme is proposed. The input degraded color image is first convert into CIELAB color space. Then two chromatic components (a* and b*) are combined to perform color cast ...
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Chapter and Conference Paper
Interactive Head 3D Reconstruction Based Combine of Key Points and Voxel
In the 3D reconstruction of the head, we can extract a large number of key points from the face, but not enough key points from the hair. The 3D reconstruction method based key points do well in the facial rec...
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Chapter and Conference Paper
Marginal Fisher Regression Classification for Face Recognition
This paper presents a novel marginal Fisher regression classification (MFRC) method by incorporating the ideas of marginal Fisher analysis (MFA) and linear regression classification (LRC). The MFRC aims at minimi...
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Chapter and Conference Paper
Weighted Deformable Part Model for Robust Human Detection
Due to human pose articulation, variation in human shapes and appearances, especially occlusion between human and objects, one challenging problem in human detection is detect partially or completely occluded ...
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Chapter and Conference Paper
Frequency Domain Directional Filtering Based Rain Streaks Removal from a Single Color Image
Bad weather conditions, such as rain or snow, degrade outdoor vision system performance. Rain removal from a single image has been investigated extensively. However, existing built rain streak models are great...
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Chapter and Conference Paper
Balance between Diversity and Relevance for Image Search Results
Image search reranking has received great attention since it overcomes the drawback of “only textual features utilization” in nowadays web-scale image search engines. Most of existing methods focus on relevanc...
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Chapter and Conference Paper
Image Search Reranking with Semi-supervised LPP and Ranking SVM
Learning to rank is one of the most popular ranking methods used in image retrieval and search reranking. However, the high-dimension of the visual features usually causes the problem of “curse of dimensionali...
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Chapter and Conference Paper
Neighborhood Preserving Projections (NPP): A Novel Linear Dimension Reduction Method
Dimension reduction is a crucial step for pattern recognition and information retrieval tasks to overcome the curse of dimensionality. In this paper a novel unsupervised linear dimension reduction method, Neighbo...
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Chapter and Conference Paper
Face Recognition Using Neighborhood Preserving Projections
Subspace learning is one of the main directions for face recognition. In this paper, a novel unsupervised subspace learning method, Neighborhood Preserving Projections (NPP), is proposed. In contrast to tradition...
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Chapter and Conference Paper
A Novel Gabor-LDA Based Face Recognition Method
In this paper, a novel face recognition method based on Gabor-wavelet and linear discriminant analysis (LDA) is proposed. Given training face images, discriminant vectors are computed using LDA. The function o...