197 Result(s)
within
Chapter
Conference Paper
Yi**ang Chen
Image Processing and Computer Vision
Pattern Recognition
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Chapter and Conference Paper
Global-to-Local Feature Mining Network for RGB-Infrared Person Re-Identification
RGB-Infrared person Re-Identification (RGB-IR ReID) is a challenging matching task that retrieves a RGB/infrared pedestrian image from the existing infrared/RGB set captured by non-overlap** visible or infra...
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Chapter and Conference Paper
Fast, Memory-Efficient Spectral Clustering with Cosine Similarity
Spectral clustering is a popular and effective method but known to face two significant challenges: scalability and out-of-sample extension. In this paper, we extend the work of Chen (ICPR 2018) on the speed s...
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Chapter and Conference Paper
MIPI 2022 Challenge on Under-Display Camera Image Restoration: Methods and Results
Develo** and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lac...
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Chapter and Conference Paper
Complex Glyph Enhancement for License Plate Generation
The complex glyphs of license plates usually comes with a long-tail distribution, leading to poor recognition performance of the tail class. Supplementing the training data with generated license plates is an ...
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Chapter and Conference Paper
UnconFuse: Avatar Reconstruction from Unconstrained Images
The report proposes an effective solution about 3D human body reconstruction from multiple unconstrained frames for ECCV 2022 WCPA Challenge: From Face, Body and Fashion to 3D Virtual avatars I (track1: Multi-...
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Chapter and Conference Paper
Continuous Spectral Reconstruction from RGB Images via Implicit Neural Representation
Existing spectral reconstruction methods learn discrete map**s from spectrally downsampled measurements (e.g., RGB images) to a specific number of spectral bands. However, they generally neglect the continuo...
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Chapter and Conference Paper
PS-NeRF: Neural Inverse Rendering for Multi-view Photometric Stereo
Traditional multi-view photometric stereo (MVPS) methods are often composed of multiple disjoint stages, resulting in noticeable accumulated errors. In this paper, we present a neural inverse rendering method ...
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Chapter and Conference Paper
RVSL: Robust Vehicle Similarity Learning in Real Hazy Scenes Based on Semi-supervised Learning
Recently, vehicle similarity learning, also called re-identification (ReID), has attracted significant attention in computer vision. Several algorithms have been developed and obtained considerable success. Ho...
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Chapter and Conference Paper
A Survey of Domain Generalization-Based Face Anti-spoofing
In recent years, remarkable research attention has been attracted to improve the generalization ability of face anti-spoofing methods, and domain generalization techniques have been widely exploited for adapti...
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Chapter and Conference Paper
Survey on Deep Learning Based Fusion Recognition of Multimodal Biometrics
We take multimodal as a new research paradigm. This research paradigm is based on the premise that all human interactions with the outside world required the support of multimodal sensory systems. Deep learnin...
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Chapter and Conference Paper
Adaptive Registration for Multi-type Remote Sensing Images via Dynamic Feature Selection
Remote sensing image registration (RSIR) has been performed in various RS applications for decades. However, how to adaptively register multi-type (multi-view, multi-temporal, and multi-sensor) RS images remai...
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Chapter and Conference Paper
Gaussian Distribution Prior Based Multi-view Self-supervised Learning for Serous Retinal Detachment Segmentation
Assessment of serous retinal detachment (SRD) plays an important role in the diagnosis of central serous chorioretinopathy (CSC). In this paper, we propose an unsupervised method, called Gaussian distribution pri...
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Chapter and Conference Paper
Hard Negative Sample Mining for Contrastive Representation in Reinforcement Learning
In recent years, contrastive learning has become an important technology of self-supervised representation learning and achieved SOTA performances in many fields, which has also gained increasing attention in ...
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Chapter and Conference Paper
Few-Shot Single-View 3D Reconstruction with Memory Prior Contrastive Network
3D reconstruction of novel categories based on few-shot learning is appealing in real-world applications and attracts increasing research interests. Previous approaches mainly focus on how to design shape prio...
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Chapter and Conference Paper
Unpaired Deep Image Dehazing Using Contrastive Disentanglement Learning
We offer a practical unpaired learning based image dehazing network from an unpaired set of clear and hazy images. This paper provides a new perspective to treat image dehazing as a two-class separated factor ...
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Chapter and Conference Paper
Hierarchical Contrastive Inconsistency Learning for Deepfake Video Detection
With the rapid development of Deepfake techniques, the capacity of generating hyper-realistic faces has aroused public concerns in recent years. The temporal inconsistency which derives from the contrast of fa...
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Chapter and Conference Paper
Uncertainty-Aware Label Rectification for Domain Adaptive Mitochondria Segmentation
Mitochondria segmentation from electron microscopy images has seen great progress, especially for learning-based methods. However, since the learning of model requires massive annotations, it is time and labou...
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Chapter and Conference Paper
Learning Neuron Stitching for Connectomics
The pipeline of connectomics usually divides the large-scale electron microscopy volumes into multiple 3D blocks and segments them independently. The segmentation results in adjacent blocks demand subtle mergi...
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Chapter and Conference Paper
Attention U-Net with Dimension-Hybridized Fast Data Density Functional Theory for Automatic Brain Tumor Image Segmentation
In the article, we proposed a hybridized method for brain tumor image segmentation by fusing topological heterogeneities of images and the attention mechanism in the neural networks. The three-dimensional imag...
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Chapter and Conference Paper
Attention Guided Slit Lamp Image Quality Assessment
Learning human visual attention into a deep convolutional network contributes to classification performance improvement. In this paper, we propose a novel attention-guided architecture for image quality assess...
