Search Results for author: Jing Jin

Found 21 papers, 11 papers with code

Tensor Decomposition based Personalized Federated Learning

no code implementations27 Aug 2022 Qing Wang, Jing Jin, Xiaofeng Liu, Huixuan Zong, Yunfeng Shao, Yinchuan Li

Federated learning (FL) is a new distributed machine learning framework that can achieve reliably collaborative training without collecting users' private data.

Model Optimization Personalized Federated Learning +1

3D Face Parsing via Surface Parameterization and 2D Semantic Segmentation Network

no code implementations18 Jun 2022 Wenyuan Sun, Ping Zhou, Yangang Wang, Zongpu Yu, Jing Jin, Guangquan Zhou

The topological disk-like 2D face image containing spatial and textural information is transformed from the sampled 3D face data through the face parameterization algorithm, and a specific 2D network called CPFNet is proposed to achieve the semantic segmentation of the 2D parameterized face data with multi-scale technologies and feature aggregation.

2D Semantic Segmentation Face Parsing +1

Light Field Depth Estimation Based on Stitched-EPI

no code implementations29 Mar 2022 Ping Zhou, Xiaoyang Liu, Jing Jin, Yuting Zhang, Junhui Hou

Depth estimation is one of the most essential problems for light field applications.

Depth Estimation

Using calibrator to improve robustness in Machine Reading Comprehension

no code implementations24 Feb 2022 Jing Jin, Houfeng Wang

Machine Reading Comprehension(MRC) has achieved a remarkable result since some powerful models, such as BERT, are proposed.

Machine Reading Comprehension Representation Learning

Content-aware Warping for View Synthesis

1 code implementation22 Jan 2022 Mantang Guo, Junhui Hou, Jing Jin, Hui Liu, Huanqiang Zeng, Jiwen Lu

To this end, we propose content-aware warping, which adaptively learns the interpolation weights for pixels of a relatively large neighborhood from their contextual information via a lightweight neural network.

Novel View Synthesis

DSSL: Deep Surroundings-person Separation Learning for Text-based Person Retrieval

1 code implementation12 Sep 2021 Aichun Zhu, Zijie Wang, Yifeng Li, Xili Wan, Jing Jin, Tian Wang, Fangqiang Hu, Gang Hua

Many previous methods on text-based person retrieval tasks are devoted to learning a latent common space mapping, with the purpose of extracting modality-invariant features from both visual and textual modality.

Person Retrieval Retrieval +2

Learning Dynamic Interpolation for Extremely Sparse Light Fields with Wide Baselines

1 code implementation ICCV 2021 Mantang Guo, Jing Jin, Hui Liu, Junhui Hou

In this paper, we tackle the problem of dense light field (LF) reconstruction from sparsely-sampled ones with wide baselines and propose a learnable model, namely dynamic interpolation, to replace the commonly-used geometry warping operation.


Occlusion-aware Unsupervised Learning of Depth from 4-D Light Fields

1 code implementation6 Jun 2021 Jing Jin, Junhui Hou

Experimental results on synthetic data show that our method can significantly shrink the performance gap between the previous unsupervised method and supervised ones, and produce depth maps with comparable accuracy to traditional methods with obviously reduced computational cost.

Depth Estimation Depth Prediction

Light Field Reconstruction via Deep Adaptive Fusion of Hybrid Lenses

1 code implementation14 Feb 2021 Jing Jin, Mantang Guo, Hui Liu, Junhui Hou, Hongkai Xiong

Besides, to promote the effectiveness of our method trained with simulated hybrid data on real hybrid data captured by a hybrid LF imaging system, we carefully design the network architecture and the training strategy.

Performance Comparison between Reconfigurable Intelligent Surface and Relays: Theoretical Methods and a Perspective from Operator

no code implementations28 Jan 2021 Qi Gu, Dan Wu, Xin Su, Jing Jin, Yifei Yuan, Jiangzhou Wang

On the other hand, a relay node in a traditional relay network has to be active, which indicates that it will consume energy when it is relaying the signal or information between the source and destination nodes.

Information Theory Information Theory

KDLSQ-BERT: A Quantized Bert Combining Knowledge Distillation with Learned Step Size Quantization

no code implementations15 Jan 2021 Jing Jin, Cai Liang, Tiancheng Wu, Liqin Zou, Zhiliang Gan

The main idea of our method is that the KD technique is leveraged to transfer the knowledge from a "teacher" model to a "student" model when exploiting LSQ to quantize that "student" model during the quantization training process.

Knowledge Distillation Language Modelling +1

Deep Selective Combinatorial Embedding and Consistency Regularization for Light Field Super-resolution

no code implementations26 Sep 2020 Jing Jin, Junhui Hou, Zhiyu Zhu, Jie Chen, Sam Kwong

To preserve the parallax structure among the reconstructed SAIs, we subsequently append a consistency regularization network trained over a structure-aware loss function to refine the parallax relationships over the coarse estimation.

Disparity Estimation Super-Resolution

Deep Spatial-angular Regularization for Compressive Light Field Reconstruction over Coded Apertures

1 code implementation ECCV 2020 Mantang Guo, Junhui Hou, Jing Jin, Jie Chen, Lap-Pui Chau

Coded aperture is a promising approach for capturing the 4-D light field (LF), in which the 4-D data are compressively modulated into 2-D coded measurements that are further decoded by reconstruction algorithms.

Image and Video Processing

Light Field Spatial Super-resolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization

1 code implementation CVPR 2020 Jing Jin, Junhui Hou, Jie Chen, Sam Kwong

Light field (LF) images acquired by hand-held devices usually suffer from low spatial resolution as the limited sampling resources have to be shared with the angular dimension.


Deep Learning-based Radiomic Features for Improving Neoadjuvant Chemoradiation Response Prediction in Locally Advanced Rectal Cancer

no code implementations9 Sep 2019 Jie Fu, Xinran Zhong, Ning li, Ritchell Van Dams, John Lewis, Kyunghyun Sung, Ann C. Raldow, Jing Jin, X. Sharon Qi

The model built with handcrafted features achieved the mean area under the ROC curve (AUC) of 0. 64, while the one built with DL-based features yielded the mean AUC of 0. 73.

Survival Prediction

Deep Coarse-to-fine Dense Light Field Reconstruction with Flexible Sampling and Geometry-aware Fusion

1 code implementation31 Aug 2019 Jing Jin, Junhui Hou, Jie Chen, Huanqiang Zeng, Sam Kwong, Jingyi Yu

Specifically, the coarse sub-aperture image (SAI) synthesis module first explores the scene geometry from an unstructured sparsely-sampled LF and leverages it to independently synthesize novel SAIs, in which a confidence-based blending strategy is proposed to fuse the information from different input SAIs, giving an intermediate densely-sampled LF.

Depth Estimation

Light Field Super-resolution via Attention-Guided Fusion of Hybrid Lenses

1 code implementation23 Jul 2019 Jing Jin, Junhui Hou, Jie Chen, Sam Kwong, Jingyi Yu

To the best of our knowledge, this is the first end-to-end deep learning method for reconstructing a high-resolution LF image with a hybrid input.


HAMLET: Interpretable Human And Machine co-LEarning Technique

no code implementations26 Mar 2018 Olivier Deiss, Siddharth Biswal, Jing Jin, Haoqi Sun, M. Brandon Westover, Jimeng Sun

Although cEEG monitoring yields large volumes of data, labeling costs and difficulty make it hard to build a classifier.

General Classification

Frequency Recognition in SSVEP-based BCI using Multiset Canonical Correlation Analysis

no code implementations26 Aug 2013 Yu Zhang, Guoxu Zhou, Jing Jin, Xingyu Wang, Andrzej Cichocki

Canonical correlation analysis (CCA) has been one of the most popular methods for frequency recognition in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs).

Electroencephalogram (EEG)

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