• Publications
  • Influence
Hedged Deep Tracking
In recent years, several methods have been developed to utilize hierarchical features learned from a deep convolutional neural network (CNN) for visual tracking. However, as features from a certainExpand
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The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking
With the advantage of high mobility, Unmanned Aerial Vehicles (UAVs) are used to fuel numerous important applications in computer vision, delivering more efficiency and convenience than surveillanceExpand
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CenterNet: Keypoint Triplets for Object Detection
In object detection, keypoint-based approaches often experience the drawback of a large number of incorrect object bounding boxes, arguably due to the lack of an additional assessment inside croppedExpand
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Cascaded Partial Decoder for Fast and Accurate Salient Object Detection
  • Zhe Wu, L. Su, Q. Huang
  • Computer Science
  • IEEE/CVF Conference on Computer Vision and…
  • 18 April 2019
Existing state-of-the-art salient object detection networks rely on aggregating multi-level features of pre-trained convolutional neural networks (CNNs). However, compared to high-level features,Expand
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Measuring visual saliency by Site Entropy Rate
In this paper, we propose a new computational model for visual saliency derived from the information maximization principle. The model is inspired by a few well acknowledged biological facts. ToExpand
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Joint Source-Channel Rate-Distortion Optimization for H.264 Video Coding Over Error-Prone Networks
For a typical video distribution system, the video contents are first compressed and then stored in the local storage or transmitted to the end users through networks. While the compressed videos areExpand
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Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion
Stereoscopic perception is an important part of human visual system that allows the brain to perceive depth. However, depth information has not been well explored in existing saliency detectionExpand
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Human Daily Action Analysis with Multi-view and Color-Depth Data
Improving human action recognition in videos is restricted by the inherent limitations of the visual data. In this paper, we take the depth information into consideration and construct a novelExpand
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RAM: A Region-Aware Deep Model for Vehicle Re-Identification
Previous works on vehicle Re-ID mainly focus on extracting global features and learning distance metrics. Because some vehicles commonly share same model and maker, it is hard to distinguish themExpand
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Fast and robust text detection in images and video frames
Text in images and video frames carries important information for visual content understanding and retrieval. In this paper, by using multiscale wavelet features, we propose a novel coarse-to-fineExpand
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