Search Results for author: Qijun Zhao

Found 21 papers, 10 papers with code

Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detection

1 code implementation5 Jul 2021 Wenbo Zhang, Ge-Peng Ji, Zhuo Wang, Keren Fu, Qijun Zhao

To tackle this dilemma and also inspired by the fact that depth quality is a key factor influencing the accuracy, we propose a novel depth quality-inspired feature manipulation (DQFM) process, which is efficient itself and can serve as a gating mechanism for filtering depth features to greatly boost the accuracy.

RGB-D Salient Object Detection Salient Object Detection

SSPNet: Scale Selection Pyramid Network for Tiny Person Detection from UAV Images

2 code implementations4 Jul 2021 Mingbo Hong, Shuiwang Li, Yuchao Yang, Feiyu Zhu, Qijun Zhao, Li Lu

With the increasing demand for search and rescue, it is highly demanded to detect objects of interest in large-scale images captured by Unmanned Aerial Vehicles (UAVs), which is quite challenging due to extremely small scales of objects.

Human Detection

Equivalence of Correlation Filter and Convolution Filter in Visual Tracking

no code implementations1 May 2021 Shuiwang Li, Qijun Zhao, Ziliang Feng, Li Lu

On the surface, correlation filter and convolution filter are usually used for different purposes.

Edge Detection Visual Tracking

Learning Residue-Aware Correlation Filters and Refining Scale Estimates with the GrabCut for Real-Time UAV Tracking

1 code implementation7 Apr 2021 Shuiwang Li, YuTing Liu, Qijun Zhao, Ziliang Feng

Unmanned aerial vehicle (UAV)-based tracking is attracting increasing attention and developing rapidly in applications such as agriculture, aviation, navigation, transportation and public security.

Watermark Faker: Towards Forgery of Digital Image Watermarking

1 code implementation23 Mar 2021 Ruowei Wang, Chenguo Lin, Qijun Zhao, Feiyu Zhu

Digital watermarking has been widely used to protect the copyright and integrity of multimedia data.

Image Generation

RGB-D Salient Object Detection via 3D Convolutional Neural Networks

1 code implementation25 Jan 2021 Qian Chen, Ze Liu, Yi Zhang, Keren Fu, Qijun Zhao, Hongwei Du

The proposed model, named RD3D, aims at pre-fusion in the encoder stage and in-depth fusion in the decoder stage to effectively promote the full integration of RGB and depth streams.

RGB-D Salient Object Detection Salient Object Detection

Light Field Salient Object Detection: A Review and Benchmark

1 code implementation10 Oct 2020 Keren Fu, Yao Jiang, Ge-Peng Ji, Tao Zhou, Qijun Zhao, Deng-Ping Fan

Secondly, we benchmark nine representative light field SOD models together with several cutting-edge RGB-D SOD models on four widely used light field datasets, from which insightful discussions and analyses, including a comparison between light field SOD and RGB-D SOD models, are achieved.

Object Detection Saliency Detection +1

The 1st Tiny Object Detection Challenge:Methods and Results

1 code implementation16 Sep 2020 Xuehui Yu, Zhenjun Han, Yuqi Gong, Nan Jiang, Jian Zhao, Qixiang Ye, Jie Chen, Yuan Feng, Bin Zhang, Xiaodi Wang, Ying Xin, Jingwei Liu, Mingyuan Mao, Sheng Xu, Baochang Zhang, Shumin Han, Cheng Gao, Wei Tang, Lizuo Jin, Mingbo Hong, Yuchao Yang, Shuiwang Li, Huan Luo, Qijun Zhao, Humphrey Shi

The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection.

Human Detection Object Detection

Siamese Network for RGB-D Salient Object Detection and Beyond

2 code implementations26 Aug 2020 Keren Fu, Deng-Ping Fan, Ge-Peng Ji, Qijun Zhao, Jianbing Shen, Ce Zhu

Inspired by the observation that RGB and depth modalities actually present certain commonality in distinguishing salient objects, a novel joint learning and densely cooperative fusion (JL-DCF) architecture is designed to learn from both RGB and depth inputs through a shared network backbone, known as the Siamese architecture.

Ranked #2 on RGB-D Salient Object Detection on SIP (using extra training data)

RGB-D Salient Object Detection Salient Object Detection +1

Towards Unsupervised Crowd Counting via Regression-Detection Bi-knowledge Transfer

no code implementations12 Aug 2020 Yuting Liu, Zheng Wang, Miaojing Shi, Shin'ichi Satoh, Qijun Zhao, Hongyu Yang

We formulate the mutual transformations between the outputs of regression- and detection-based models as two scene-agnostic transformers which enable knowledge distillation between the two models.

Crowd Counting Knowledge Distillation +2

Audio-based automatic mating success prediction of giant pandas

no code implementations24 Dec 2019 WeiRan Yan, MaoLin Tang, Qijun Zhao, Peng Chen, Dunwu Qi, Rong Hou, Zhihe Zhang

Giant pandas, stereotyped as silent animals, make significantly more vocal sounds during breeding season, suggesting that sounds are essential for coordinating their reproduction and expression of mating preference.

Distinguishing Individual Red Pandas from Their Faces

no code implementations9 Aug 2019 Qi He, Qijun Zhao, Ning Liu, Peng Chen, Zhihe Zhang, Rong Hou

We are going to release our database and model in the public domain to promote the research on automatic animal identification and particularly on the technique for protecting red pandas.

Point in, Box out: Beyond Counting Persons in Crowds

no code implementations CVPR 2019 Yuting Liu, Miaojing Shi, Qijun Zhao, Xiaofang Wang

In the end, we propose a curriculum learning strategy to train the network from images of relatively accurate and easy pseudo ground truth first.

Crowd Counting Curriculum Learning

Robust Face Recognition with Deeply Normalized Depth Images

no code implementations1 May 2018 Ziqing Feng, Qijun Zhao

The PEN depth image is finally passed to $Net_{F}$, which extracts a robust feature representation via another DCNN for face recognition.

Face Recognition Robust Face Recognition

Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition

no code implementations CVPR 2018 Feng Liu, Ronghang Zhu, Dan Zeng, Qijun Zhao, Xiaoming Liu

This paper proposes an encoder-decoder network to disentangle shape features during 3D face reconstruction from single 2D images, such that the tasks of reconstructing accurate 3D face shapes and learning discriminative shape features for face recognition can be accomplished simultaneously.

3D Face Reconstruction Face Identification +1

Evaluation of Dense 3D Reconstruction from 2D Face Images in the Wild

no code implementations14 Mar 2018 Zhen-Hua Feng, Patrik Huber, Josef Kittler, Peter JB Hancock, Xiao-Jun Wu, Qijun Zhao, Paul Koppen, Matthias Rätsch

To this end, we organise a competition that provides a new benchmark dataset that contains 2000 2D facial images of 135 subjects as well as their 3D ground truth face scans.

3D Face Reconstruction 3D Reconstruction +1

Joint Face Alignment and 3D Face Reconstruction with Application to Face Recognition

no code implementations9 Aug 2017 Feng Liu, Qijun Zhao, Xiaoming Liu, Dan Zeng

Extensive experiments show that the proposed method can achieve the state-of-the-art accuracy in both face alignment and 3D face reconstruction, and benefit face recognition owing to its reconstructed PEN 3D face.

3D Face Reconstruction Face Alignment +1

Effective face landmark localization via single deep network

no code implementations9 Feb 2017 Zongping Deng, Ke Li, Qijun Zhao, Yi Zhang, Hu Chen

In this paper, we propose a novel face alignment method using single deep network (SDN) on existing limited training data.

Data Augmentation Face Alignment

On 3D Face Reconstruction via Cascaded Regression in Shape Space

no code implementations21 Sep 2015 Feng Liu, Dan Zeng, Jing Li, Qijun Zhao

Cascaded regression has been recently applied to reconstructing 3D faces from single 2D images directly in shape space, and achieved state-of-the-art performance.

3D Face Reconstruction

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