Search Results for author: Jing Jin

Found 27 papers, 13 papers with code

DIVESPOT: Depth Integrated Volume Estimation of Pile of Things Based on Point Cloud

no code implementations7 Jul 2024 Yiran Ling, Rongqiang Zhao, Yixuan Shen, Dongbo Li, Jing Jin, Jie Liu

However, using existing method for these scenarios is challenged by unstable measurement poses, significant light interference, the difficulty of training data collection, and the computational burden brought by large piles.

A Label-Free and Non-Monotonic Metric for Evaluating Denoising in Event Cameras

no code implementations13 Jun 2024 Chenyang Shi, Shasha Guo, Boyi Wei, Hanxiao Liu, Yibo Zhang, Ningfang Song, Jing Jin

To overcome these limitations, we propose the first label-free and non-monotonic evaluation metric, the area of the continuous contrast curve (AOCC), which utilizes the area enclosed by event frame contrast curves across different time intervals.

Denoising valid

InstructPipe: Building Visual Programming Pipelines with Human Instructions

no code implementations15 Dec 2023 Zhongyi Zhou, Jing Jin, Vrushank Phadnis, Xiuxiu Yuan, Jun Jiang, Xun Qian, Jingtao Zhou, Yiyi Huang, Zheng Xu, yinda zhang, Kristen Wright, Jason Mayes, Mark Sherwood, Johnny Lee, Alex Olwal, David Kim, Ram Iyengar, Na Li, Ruofei Du

Our user study (N=16) showed that InstructPipe empowers novice users to streamline their workflow in creating desired ML pipelines, reduce their learning curve, and spark innovative ideas with open-ended commands.

Multistatic Integrated Sensing and Communication System in Cellular Networks

no code implementations22 May 2023 Zixiang Han, Lincong Han, Xiaozhou Zhang, Yajuan Wang, Liang Ma, Mengting Lou, Jing Jin, Guangyi Liu

A novel multistatic multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system in cellular networks is proposed.

Position

IDO-VFI: Identifying Dynamics via Optical Flow Guidance for Video Frame Interpolation with Events

1 code implementation17 May 2023 Chenyang Shi, Hanxiao Liu, Jing Jin, Wenzhuo Li, Yuzhen Li, Boyi Wei, Yibo Zhang

The proposed method first estimates the optical flow based on frames and events, and then decides whether to further calculate the residual optical flow in those sub-regions via a Gumbel gating module according to the optical flow amplitude.

Event-based Optical Flow Optical Flow Estimation +1

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.

Diversity Model Optimization +2

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 via Stitched Epipolar Plane Images

1 code implementation29 Mar 2022 Ping Zhou, Langqing Shi, Xiaoyang Liu, Jing Jin, Yuting Zhang, Junhui Hou

This strategy involves determining the depth of such regions by progressing from the edges towards the interior, prioritizing accurate regions over coarse regions.

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.

SSIM

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, Junhui Hou, Hui Liu, 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.

Super-Resolution

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.

Computational Efficiency 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.

Super-Resolution

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).

EEG SSVEP

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