Search Results for author: Xin Deng

Found 20 papers, 10 papers with code

HiGraphDTI: Hierarchical Graph Representation Learning for Drug-Target Interaction Prediction

no code implementations16 Apr 2024 Bin Liu, Siqi Wu, Jin Wang, Xin Deng, Ao Zhou

Specifically, HiGraphDTI learns hierarchical drug representations from triple-level molecular graphs to thoroughly exploit chemical information embedded in atoms, motifs, and molecules.

Graph Representation Learning molecular representation

Enhancing Quality of Compressed Images by Mitigating Enhancement Bias Towards Compression Domain

no code implementations27 Feb 2024 Qunliang Xing, Mai Xu, Shengxi Li, Xin Deng, Meisong Zheng, Huaida Liu, Ying Chen

However, these methods exhibit a pervasive enhancement bias towards the compression domain, inadvertently regarding it as more realistic than the raw domain.

Pixel Adapter: A Graph-Based Post-Processing Approach for Scene Text Image Super-Resolution

1 code implementation16 Sep 2023 Wenyu Zhang, Xin Deng, Baojun Jia, Xingtong Yu, Yifan Chen, Jin Ma, Qing Ding, Xinming Zhang

Additionally, we introduce the MLP-based Sequential Residual Block (MSRB) for robust feature extraction from text images, and a Local Contour Awareness loss ($\mathcal{L}_{lca}$) to enhance the model's perception of details.

Graph Attention Image Super-Resolution

Improving Grounded Language Understanding in a Collaborative Environment by Interacting with Agents Through Help Feedback

no code implementations21 Apr 2023 Nikhil Mehta, Milagro Teruel, Patricio Figueroa Sanz, Xin Deng, Ahmed Hassan Awadallah, Julia Kiseleva

We explore multiple types of help players can give to the AI to guide it and analyze the impact of this help in AI behavior, resulting in performance improvements.

Neural Characteristic Function Learning for Conditional Image Generation

1 code implementation ICCV 2023 Shengxi Li, Jialu Zhang, Yifei Li, Mai Xu, Xin Deng, Li Li

The emergence of conditional generative adversarial networks (cGANs) has revolutionised the way we approach and control the generation, by means of adversarially learning joint distributions of data and auxiliary information.

Conditional Image Generation Generative Adversarial Network

PIRNet: Privacy-Preserving Image Restoration Network via Wavelet Lifting

no code implementations ICCV 2023 Xin Deng, Chao GAO, Mai Xu

In this paper, we propose a novel method namely PIRNet, which operates privacy-preserving image restoration in the steganographic domain.

Deblurring Image Denoising +3

DAQE: Enhancing the Quality of Compressed Images by Exploiting the Inherent Characteristic of Defocus

1 code implementation20 Nov 2022 Qunliang Xing, Mai Xu, Xin Deng, Yichen Guo

Image defocus is inherent in the physics of image formation caused by the optical aberration of lenses, providing plentiful information on image quality.

Making Large Language Models Interactive: A Pioneer Study on Supporting Complex Information-Seeking Tasks with Implicit Constraints

no code implementations2 May 2022 Ali Ahmadvand, Negar Arabzadeh, Julia Kiseleva, Patricio Figueroa Sanz, Xin Deng, Sujay Jauhar, Michael Gamon, Eugene Agichtein, Ned Friend, Aniruddha

Current interactive systems with natural language interfaces lack the ability to understand a complex information-seeking request which expresses several implicit constraints at once, and there is no prior information about user preferences e. g.,"find hiking trails around San Francisco which are accessible with toddlers and have beautiful scenery in summer", where output is a list of possible suggestions for users to start their exploration.

Hallucination Retrieval

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.

Saliency Prediction

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

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

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.

Clustering Cultural Vocal Bursts Intensity Prediction +2

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

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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