24 Result(s)
within
Computer Science
Image Processing and Computer Vision
Pattern Recognition
**hai Yu
Conference Paper
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Chapter and Conference Paper
Revisiting TENT for Test-Time Adaption Semantic Segmentation and Classification Head Adjustment
Test-time adaption is very effective at solving the domain shift problem where the training data and testing data are sampled from different domains. However, most test-time adaption methods made their success...
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Chapter and Conference Paper
Enhancing Adversarial Transferability from the Perspective of Input Loss Landscape
The transferability of adversarial examples enables the black-box attacks and poses a threat to the application of deep neural networks in real-world, which has attracted great attention in recent years. Regar...
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Chapter and Conference Paper
Affinity-Aware Relation Network for Oriented Object Detection in Aerial Images
Object detection in aerial images is a challenging task due to the oriented and densely packed objects. However, densely packed objects constitute a significant characteristic of aerial images: objects are not...
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Chapter and Conference Paper
Talking Face Video Generation with Editable Expression
In rencent years, the convolutional neural network have been proved to be a great success in generating talking face. Existing methods have combined a single face image with speech to generate talking face vid...
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Chapter and Conference Paper
Towards More Powerful Multi-column Convolutional Network for Crowd Counting
Scale variation has always been one of the most challenging problems for crowd counting. By using multi-column convolutions with different receptive fields to deal with different scales in the scene, the multi...
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Chapter and Conference Paper
UDC 2020 Challenge on Image Restoration of Under-Display Camera: Methods and Results
This paper is the report of the first Under-Display Camera (UDC) image restoration challenge in conjunction with the RLQ workshop at ECCV 2020. The challenge is based on a newly-collected database of Under-Dis...
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Chapter and Conference Paper
Secure Image Denoising over Two Clouds
Multimedia processing with cloud is prevalent now, which the cloud server can provide abundant resources to processing various multimedia processing tasks. However, some privacy issues must be considered in cl...
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Chapter and Conference Paper
TCCF: Tracking Based on Convolutional Neural Network and Correlation Filters
With the rapid development of deep learning in recent years, lots of trackers based on deep learning were proposed, and achieved great improvements compared with traditional methods. However, due to the scarci...
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Chapter and Conference Paper
A Saliency Based Human Detection Framework for Infrared Thermal Images
In this paper, a novel saliency framework for crowd detection in infrared thermal images is proposed. In order to obtain the optimal classifier from a large amount of data, the process of training consists of ...
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Chapter and Conference Paper
Key-Region Representation Learning for Anomaly Detection
Anomaly detection and localization is of great importance for public safety monitoring. In this paper we focus on individual behavior anomaly detection, which remains a challenging problem due to complicated d...
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Chapter and Conference Paper
Deep Scale Feature for Visual Tracking
Recently, deep learning methods have been introduced to the field of visual tracking and gain promising results due to the property of complicated feature. However existing deep learning trackers use pre-train...
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Chapter and Conference Paper
PPEDNet: Pyramid Pooling Encoder-Decoder Network for Real-Time Semantic Segmentation
Image semantic segmentation is a fundamental problem and plays an important role in computer vision and artificial intelligence. Recent deep neural networks have improved the accuracy of semantic segmentation ...
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Chapter and Conference Paper
Semi-supervised Learning for Human Pose Recognition with RGB-D Light-Model
This work targets human pose recognition based on RGB-D videos. In recently, RGB-D based methods can be typically represented as either maps-based approaches or skeleton-based approaches. This paper proposes a...
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Chapter and Conference Paper
Improve Neural Network Using Saliency
In traditional neural networks for image classification, every input image pixel is treated the same way. However real human visual system tends pay more attention to what they really focus on. This paper prop...
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Chapter and Conference Paper
Multi-target Tracking via Max-Entropy Target Selection and Heterogeneous Camera Fusion
Nowadays, dual-camera systems, which consist of a static camera and a pan-tilt-zoom (PTZ) camera, have become popular in video surveillance, since they can offer wide area coverage and highly detailed images o...
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Chapter and Conference Paper
Moving Object Segmentation by Length-Unconstrained Trajectory Analysis
Background subtraction for moving cameras is an unsolved key problem in intelligent video analysis. Trajectory analysis has demonstrated a significant difference between background and foreground motion model....
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Chapter and Conference Paper
A Robust Occlusion Judgment Scheme for Target Tracking Under the Framework of Particle Filter
In traffic surveillance system, it is still a challenging issue to track an occluded vehicle continuously and accurately, especially under total occlusion situations. Occlusion judgment is critical in occluded...
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Chapter and Conference Paper
News Event Detection Based Web Big Data
News event detection is also called TDT (Topic Detection and Tracking), which is hot research field. Previous studies about TDT are general based on news headline. However, the headline in certain situations c...
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Chapter and Conference Paper
Cooperative Target Tracking in Dual-Camera System with Bidirectional Information Fusion
The Dual-Camera system which consists of a static camera and a pan-tilt-zoom (PTZ) camera, plays an importance role in public area monitoring. The superiority of this system lies in that it can offer wide area...
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Chapter and Conference Paper
Crowd Tracking with Dynamic Evolution of Group Structures
Crowd tracking generates trajectories of a set of particles for further analysis of crowd motion patterns. In this paper, we try to answer the following questions: what are the particles appropriate for crowd ...
