no code implementations • 24 May 2020 • Zhiguo Wang, Zhongliang Yang, Yu-Jin Zhang
First, the aggregation strategy chooses one detector as master detector by experience, and sets the remaining detectors as auxiliary detectors.
1 code implementation • 3 Apr 2020 • Wentian Li, Xidong Feng, Haotian An, Xiang Yao Ng, Yu-Jin Zhang
In this work, we propose a deep reinforcement learning based method to reconstruct the corrupted images with meaningful pixel-wise operations (e. g. edge enhancing filters), so that the reconstruction process is transparent to users.
no code implementations • 19 Nov 2019 • Zhiguo Wang, Zhongliang Yang, Yu-Jin Zhang
To address these problems, we propose a promotion method: utilize the maximum of block-level GEs on the frame to detect anomaly.
no code implementations • 4 Feb 2019 • Zhongliang Yang, Hao Yang, Yuting Hu, Yongfeng Huang, Yu-Jin Zhang
To solve these two challenges, in this paper, combined with the sliding window detection algorithm and Convolution Neural Network we propose a real-time VoIP steganalysis method which based on multi-channel convolution sliding windows.
no code implementations • 3 Dec 2018 • Lijun Zhang, Yu-Jin Zhang, Yongbin Gao
It is well known that the generative adversarial nets (GANs) are remarkably difficult to train.
no code implementations • ECCV 2018 • Xiangyu Xu, Deqing Sun, Sifei Liu, Wenqi Ren, Yu-Jin Zhang, Ming-Hsuan Yang, Jian Sun
Specifically, we first exploit Convolutional Neural Networks to estimate the relative depth and portrait segmentation maps from a single input image.
no code implementations • 6 May 2018 • Lijun Zhang, Yongbin Gao, Yu-Jin Zhang
This paper proposes a scheme for single image haze removal based on the airlight field (ALF) estimation.
no code implementations • ICCV 2017 • Xiangyu Xu, Deqing Sun, Jinshan Pan, Yu-Jin Zhang, Hanspeter Pfister, Ming-Hsuan Yang
We present an algorithm to directly restore a clear high-resolution image from a blurry low-resolution input.
no code implementations • 8 Jun 2017 • Zhongliang Yang, Yu-Jin Zhang, Sadaqat ur Rehman, Yongfeng Huang
Automatically generating a natural language description of an image is a task close to the heart of image understanding.
no code implementations • 13 Sep 2014 • Yin Zheng, Yu-Jin Zhang, Hugo Larochelle
Second, we propose a deep extension of our model and provide an efficient way of training the deep model.
no code implementations • 9 Jun 2014 • Xue Li, Yu-Jin Zhang, Bin Shen, Bao-Di Liu
A novel tag completion algorithm is proposed in this paper, which is designed with the following features: 1) Low-rank and error s-parsity: the incomplete initial tagging matrix D is decomposed into the complete tagging matrix A and a sparse error matrix E. However, instead of minimizing its nuclear norm, A is further factor-ized into a basis matrix U and a sparse coefficient matrix V, i. e. D=UV+E.
no code implementations • 3 Jun 2014 • Shasha Bu, Yu-Jin Zhang
A novel representation of images for image retrieval is introduced in this paper, by using a new type of feature with remarkable discriminative power.
no code implementations • CVPR 2014 • Yin Zheng, Yu-Jin Zhang, Hugo Larochelle
Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to deal with multimodal data, such as in image annotation tasks.
no code implementations • 23 May 2013 • Yin Zheng, Yu-Jin Zhang, Hugo Larochelle
Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to perform scene recognition and annotation.