Search Results for author: Xin Deng

Found 10 papers, 7 papers with code

Joint Learning of Visual-Audio Saliency Prediction and Sound Source Localization on Multi-face Videos

1 code implementation5 Nov 2021 Minglang Qiao, Yufan Liu, Mai Xu, Xin Deng, Bing Li, Weiming Hu, Ali Borji

In this paper, we propose a multitask learning method for visual-audio saliency prediction and sound source localization on multi-face video by leveraging visual, audio and face information.

Eye Tracking Saliency Prediction

Deep Homography for Efficient Stereo Image Compression

1 code implementation CVPR 2021 Xin Deng, Wenzhe Yang, Ren Yang, Mai Xu, Enpeng Liu, Qianhan Feng, Radu Timofte

To fully explore the mutual information across two stereo images, we use a deep regression model to estimate the homography matrix, i. e., H matrix.

Image Compression

LAU-Net: Latitude Adaptive Upscaling Network for Omnidirectional Image Super-Resolution

no code implementations CVPR 2021 Xin Deng, Hao Wang, Mai Xu, Yichen Guo, Yuhang Song, Li Yang

In addition, we propose a deep reinforcement learning scheme with a latitude adaptive reward, in order to automatically select optimal upscaling factors for different latitude bands.

Image Super-Resolution

HiNet: Deep Image Hiding by Invertible Network

1 code implementation ICCV 2021 Junpeng Jing, Xin Deng, Mai Xu, Jianyi Wang, Zhenyu Guan

Capacity, invisibility and security are three primary challenges in image hiding task.

Semi-Supervised Learning Approach to Discover Enterprise User Insights from Feedback and Support

no code implementations18 Jul 2020 Xin Deng, Ross Smith, Genevieve Quintin

In this paper, we proposed and developed an innovative Semi-Supervised Learning approach by utilizing Deep Learning and Topic Modeling to have a better understanding of the user voice. This approach combines a BERT-based multiclassification algorithm through supervised learning combined with a novel Probabilistic and Semantic Hybrid Topic Inference (PSHTI) Model through unsupervised learning, aiming at automating the process of better identifying the main topics or areas as well as the sub-topics from the textual feedback and support. There are three major break-through: 1.

Topic Models Transfer Learning

Deep Convolutional Neural Network for Multi-modal Image Restoration and Fusion

no code implementations9 Oct 2019 Xin Deng, Pier Luigi Dragotti

In this paper, we propose a novel deep convolutional neural network to solve the general multi-modal image restoration (MIR) and multi-modal image fusion (MIF) problems.

Image Denoising Image Reconstruction +3

Wavelet Domain Style Transfer for an Effective Perception-distortion Tradeoff in Single Image Super-Resolution

1 code implementation ICCV 2019 Xin Deng, Ren Yang, Mai Xu, Pier Luigi Dragotti

In this paper, we propose a novel method based on wavelet domain style transfer (WDST), which achieves a better PD tradeoff than the GAN based methods.

Image Super-Resolution Style Transfer

Multimodal Image Super-resolution via Joint Sparse Representations induced by Coupled Dictionaries

1 code implementation25 Sep 2017 Pingfan Song, Xin Deng, João F. C. Mota, Nikos Deligiannis, Pier Luigi Dragotti, Miguel R. D. Rodrigues

This paper proposes a new approach to construct a high-resolution (HR) version of a low-resolution (LR) image given another HR image modality as reference, based on joint sparse representations induced by coupled dictionaries.

Dictionary Learning Image Super-Resolution

Reducing Complexity of HEVC: A Deep Learning Approach

1 code implementation19 Sep 2017 Mai Xu, Tianyi Li, Zulin Wang, Xin Deng, Ren Yang, Zhenyu Guan

Therefore, this paper proposes a deep learning approach to predict the CU partition for reducing the HEVC complexity at both intra- and inter-modes, which is based on convolutional neural network (CNN) and long- and short-term memory (LSTM) network.

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