no code implementations • 26 Sep 2024 • Zehao Zhu, Wei Sun, Jun Jia, Wei Wu, Sibin Deng, Kai Li, Ying Chen, Xiongkuo Min, Jia Wang, Guangtao Zhai
For the subjective QoE study, we introduce the first live video streaming QoE dataset, TaoLive QoE, which consists of $42$ source videos collected from real live broadcasts and $1, 155$ corresponding distorted ones degraded due to a variety of streaming distortions, including conventional streaming distortions such as compression, stalling, as well as live streaming-specific distortions like frame skipping, variable frame rate, etc.
no code implementations • 3 Sep 2024 • Haoran Wei, Chenglong Liu, Jinyue Chen, Jia Wang, Lingyu Kong, Yanming Xu, Zheng Ge, Liang Zhao, Jianjian Sun, Yuang Peng, Chunrui Han, Xiangyu Zhang
As an OCR-2. 0 model, GOT can handle all the above "characters" under various OCR tasks.
1 code implementation • Expert Systems with Applications 2024 • Jia Wang, Marvin John Ignacio, Seunghee Yu, Hulin Jin, Yong-Guk Kim
One of the core components in the recommender systems is a sequential model with which an input sequence is transformed into the predicted items.
1 code implementation • 28 Jun 2024 • Yubo Huang, Jia Wang, Peipei Li, Liuyu Xiang, Peigang Li, Zhaofeng He
In this work, we propose a generative iris prior embedded Transformer model (Gformer), in which we build a hierarchical encoder-decoder network employing Transformer block and generative iris prior.
2 code implementations • 28 Jun 2024 • Jihao Liu, Xin Huang, Jinliang Zheng, Boxiao Liu, Jia Wang, Osamu Yoshie, Yu Liu, Hongsheng Li
This paper introduces MM-Instruct, a large-scale dataset of diverse and high-quality visual instruction data designed to enhance the instruction-following capabilities of large multimodal models (LMMs).
Ranked #107 on Visual Question Answering on MM-Vet
no code implementations • 22 Jun 2024 • Shiqi Gao, Huiyu Duan, Xinyue Li, Kang Fu, Yicong Peng, Qihang Xu, Yuanyuan Chang, Jia Wang, Xiongkuo Min, Guangtao Zhai
In this paper, we propose a quality-guided image enhancement paradigm that enables image enhancement models to learn the distribution of images with various quality ratings.
no code implementations • 17 May 2024 • Bo Wu, Peiye Liu, Wen-Huang Cheng, Bei Liu, Zhaoyang Zeng, Jia Wang, Qiushi Huang, Jiebo Luo
The research progress analysis provides an overall analysis of the solutions and trends in recent years.
no code implementations • 24 Apr 2024 • Ziheng Chen, Jia Wang, Jun Zhuang, Abbavaram Gowtham Reddy, Fabrizio Silvestri, Jin Huang, Kaushiki Nag, Kun Kuang, Xin Ning, Gabriele Tolomei
This bias emerges from two main sources: (1) data-level bias, characterized by uneven data removal, and (2) algorithm-level bias, which leads to the contamination of the remaining dataset, thereby degrading model accuracy.
no code implementations • 23 Apr 2024 • Guangpeng Fan, Fei Yan, Xiangquan Zeng, Qingtao Xu, Ruoyoulan Wang, Binghong Zhang, Jialing Zhou, Liangliang Nan, Jinhu Wang, Zhiwei Zhang, Jia Wang
We proposed a method to map the canopy height of the primeval forest within the world-level giant tree distribution area by using a spaceborne LiDAR fusion satellite imagery (Global Ecosystem Dynamics Investigation (GEDI), ICESat-2, and Sentinel-2) driven deep learning modeling.
1 code implementation • 26 Mar 2024 • Haiyang Zhang, Qiuyi Chen, Yuanjie Zou, Yushan Pan, Jia Wang, Mark Stevenson
The Document Set Expansion (DSE) task involves identifying relevant documents from large collections based on a limited set of example documents.
no code implementations • 22 Mar 2024 • Yuhan Xia, Qingqing Zhao, Yunfei Long, Ge Xu, Jia Wang
In traditional research approaches, sensory perception and emotion classification have traditionally been considered separate domains.
no code implementations • 20 Jan 2024 • Haiyang Zhang, Qiuyi Chen, Yuanjie Zou, Yushan Pan, Jia Wang, Mark Stevenson
Previous work shows that PU learning is a promising method for this task.
no code implementations • 3 Jan 2024 • Kang Fu, Yicong Peng, ZiCheng Zhang, Qihang Xu, Xiaohong Liu, Jia Wang, Guangtao Zhai
Subsequently, the attention fusion module integrates the image feature with the priori attention feature obtained during training to generate image-adaptive canonical polyadic tensors.
1 code implementation • CVPR 2024 • Xin Fan, Xiaolin Wang, Jiaxin Gao, Jia Wang, Zhongxuan Luo, Risheng Liu
One prevalent method to address one-shot MIS is joint registration and segmentation (JRS) with a shared encoder which mainly explores the voxel-wise correspondence between the labeled data and unlabeled data for better segmentation.
no code implementations • 21 Dec 2023 • Jia Wang, Leander Hemelhof, Ivan Markovsky, Panagiotis Patrinos
This paper studies data-driven iterative learning control (ILC) for linear time-invariant (LTI) systems with unknown dynamics, output disturbances and input box-constraints.
no code implementations • 2 Nov 2023 • Weikang Chen, Junping Du, Yingxia Shao, Jia Wang, Yangxi Zhou
Federated learning enables a collaborative training and optimization of global models among a group of devices without sharing local data samples.
no code implementations • 28 Jul 2023 • Kang Fu, Xiaohong Liu, Jun Jia, ZiCheng Zhang, Yicong Peng, Jia Wang, Guangtao Zhai
To achieve end-to-end training of the framework, we integrate a neural network that simulates the ISP pipeline to handle the RAW-to-RGB conversion process.
no code implementations • 27 Jun 2023 • Junwei Yin, Min Gao, Kai Shu, Zehua Zhao, Yinqiu Huang, Jia Wang
To this end, we propose an approach of Emulating the behaviors of readers (Ember) for fake news detection on social media, incorporating readers' reading and verificating process to model news from the component perspective thoroughly.
no code implementations • 13 Jun 2023 • Lan Wang, Ruiling He, Lili Zhao, Jia Wang, Zhengzi Geng, Tao Ren, Guo Zhang, Peng Zhang, Kaiqiang Tang, Chaofei Gao, Fei Chen, Liting Zhang, Yonghe Zhou, Xin Li, Fanbin He, Hui Huan, Wenjuan Wang, Yunxiao Liang, Juan Tang, Fang Ai, Tingyu Wang, Liyun Zheng, Zhongwei Zhao, Jiansong Ji, Wei Liu, Jiaojiao Xu, Bo Liu, Xuemei Wang, Yao Zhang, Qiong Yan, Muhan Lv, Xiaomei Chen, Shuhua Zhang, Yihua Wang, Yang Liu, Li Yin, Yanni Liu, Yanqing Huang, Yunfang Liu, Kun Wang, Meiqin Su, Li Bian, Ping An, Xin Zhang, Linxue Qian, Shao Li, Xiaolong Qi
Validation analysis revealed that the AUCs of DLRP were 0. 91 for GEV (95% CI 0. 90 to 0. 93, p < 0. 05) and 0. 88 for HRV (95% CI 0. 86 to 0. 89, p < 0. 01), which were significantly and robustly better than canonical risk indicators, including the value of LSM and SSM.
no code implementations • 30 Apr 2023 • Ziheng Chen, Fabrizio Silvestri, Jia Wang, Yongfeng Zhang, Gabriele Tolomei
By reversing the learning process of the recommendation model, we thus develop a proficient greedy algorithm to generate fabricated user profiles and their associated interaction records for the aforementioned surrogate model.
no code implementations • 31 Mar 2023 • Yanjie Dong, Luya Wang, Yuanfang Chi, Jia Wang, Haijun Zhang, Fei Richard Yu, Victor C. M. Leung, Xiping Hu
A wireless federated learning system is investigated by allowing a server and workers to exchange uncoded information via orthogonal wireless channels.
1 code implementation • 30 Mar 2023 • Huiyu Duan, Wei Shen, Xiongkuo Min, Danyang Tu, Long Teng, Jia Wang, Guangtao Zhai
Recently, masked autoencoders (MAE) for feature pre-training have further unleashed the potential of Transformers, leading to state-of-the-art performances on various high-level vision tasks.
Ranked #4 on Image Defocus Deblurring on DPD (Dual-view)
no code implementations • 17 Sep 2022 • Chenyi Liu, Fei Chen, Lu Deng, Renjiao Yi, Lintao Zheng, Chenyang Zhu, Jia Wang, Kai Xu
We introduce a well-targeted down-sampling strategy that focuses more on edge area for efficient feature extraction of complex geometry.
no code implementations • 4 Aug 2022 • Ziheng Chen, Fabrizio Silvestri, Jia Wang, Yongfeng Zhang, Zhenhua Huang, Hongshik Ahn, Gabriele Tolomei
Although powerful, it is very difficult for a GNN-based recommender system to attach tangible explanations of why a specific item ends up in the list of suggestions for a given user.
no code implementations • 28 Jun 2022 • Naifu Zhang, Meixia Tao, Jia Wang, Fan Xu
One of the main focuses in distributed learning is communication efficiency, since model aggregation at each round of training can consist of millions to billions of parameters.
no code implementations • 5 Jun 2022 • Jia Wang, Junping Du, Yingxia Shao, Ang Li
In this paper, we study the text sentiment classification of online travel reviews based on social media online comments and propose the SCCL model based on capsule network and sentiment lexicon.
no code implementations • 27 Jan 2022 • Jia Wang, Hongwei Zhu, Jiancheng Shen, Yu Cao, Benyuan Liu
It is a challenging task to predict financial markets.
no code implementations • 27 Jan 2022 • Xizhe Wang, Ning Zhang, Jia Wang, Jing Ni, Xinzi Sun, John Zhang, Zitao Liu, Yu Cao, Benyuan Liu
To improve the IVF success rate, we propose a knowledge-based decision support system that can provide medical advice on the treatment protocol and medication adjustment for each patient visit during IVF treatment cycle.
no code implementations • NeurIPS 2021 • Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg
Energy-based models (EBMs) provide an elegant framework for density estimation, but they are notoriously difficult to train.
1 code implementation • 22 Oct 2021 • Ziheng Chen, Fabrizio Silvestri, Jia Wang, He Zhu, Hongshik Ahn, Gabriele Tolomei
However, existing CF generation methods either exploit the internals of specific models or depend on each sample's neighborhood, thus they are hard to generalize for complex models and inefficient for large datasets.
no code implementations • 15 May 2021 • Lei Sun, Jia Wang, Kailun Yang, Kaikai Wu, Xiangdong Zhou, Kaiwei Wang, Jian Bai
A lightweight panoramic annular semantic segmentation neural network model is designed to achieve high-accuracy and real-time scene parsing.
Ranked #77 on Semantic Segmentation on Cityscapes val
no code implementations • 18 Apr 2021 • Jia Wang, Ping Wang, Biao Li, Ruigang Fu, Junzheng Wu
The Discriminative Optimization (DO) algorithm has been proved much successful in 3D point cloud registration.
no code implementations • 8 Apr 2021 • Jia Wang, Tong Sun, Benyuan Liu, Yu Cao, Hongwei Zhu
Financial markets are a complex dynamical system.
no code implementations • 5 Apr 2021 • Jia Wang, Tong Sun, Benyuan Liu, Yu Cao, Degang Wang
Financial markets are difficult to predict due to its complex systems dynamics.
no code implementations • 21 Jan 2021 • Naifu Zhang, Meixia Tao, Jia Wang
In FL, however, the model update is an indirect multi-terminal source coding problem, also called as the CEO problem where each edge device cannot observe directly the gradient that is to be reconstructed at the decoder, but is rather provided only with a noisy version.
no code implementations • 8 Dec 2020 • Shuyu Kong, You Li, Jia Wang, Amin Rezaei, Hai Zhou
Inspired by the robustness of K-Nearest Neighbors (KNN) against data noise, in this work, we propose to apply deep KNN for label cleanup.
1 code implementation • 23 Nov 2020 • Jia Wang, Ping Wang, Biao Li, Yinghui Gao, Siyi Zhao
As the search space of registration is usually non-convex, the optimization algorithm, which aims to search the best transformation parameters, is a challenging step.
no code implementations • 23 Sep 2020 • Cong Geng, Jia Wang, Li Chen, Zhiyong Gao
Variational Autoencoder (VAE) and its variations are classic generative models by learning a low-dimensional latent representation to satisfy some prior distribution (e. g., Gaussian distribution).
no code implementations • 12 Feb 2020 • Cong Geng, Jia Wang, Li Chen, Wenbo Bao, Chu Chu, Zhiyong Gao
Based on this defined Riemannian metric, we introduce a constant speed loss and a minimizing geodesic loss to regularize the interpolation network to generate uniform interpolation along the learned geodesic on the manifold.
no code implementations • CVPR 2020 • Song Tao, Jia Wang
In order to alleviate the notorious mode collapse phenomenon in generative adversarial networks (GANs), we propose a novel training method of GANs in which certain fake samples are considered as real ones during the training process.
no code implementations • 4 Aug 2019 • Tian Zhang, Jia Wang, Yihang Dan, Yuxiang Lanqiu, Jian Dai, Xu Han, Xiaojuan Sun, Kun Xu
Recently, optical neural networks (ONNs) integrated in photonic chips has received extensive attention because they are expected to implement the same pattern recognition tasks in the electronic platforms with high efficiency and low power consumption.
Ranked #1 on Reinforcement Learning on iris (using extra training data)
no code implementations • 10 Jul 2018 • Huangjie Zheng, Jiangchao Yao, Ya zhang, Ivor W. Tsang, Jia Wang
In information theory, Fisher information and Shannon information (entropy) are respectively used to quantify the uncertainty associated with the distribution modeling and the uncertainty in specifying the outcome of given variables.
1 code implementation • 3 Dec 2017 • Hongwei Wang, Jia Wang, Miao Zhao, Jiannong Cao, Minyi Guo
JTS-MF model calculates similarity among users and votings by combining their TEWE representation and structural information of social networks, and preserves this topic-semantic-social similarity during matrix factorization.
1 code implementation • 28 Nov 2017 • Jia Wang, Vincent W. Zheng, Zemin Liu, Kevin Chen-Chuan Chang
As a result, we introduce a new data model, namely diffusion topologies, to fully describe the cascade structure.
5 code implementations • 22 Nov 2017 • Hongwei Wang, Jia Wang, Jialin Wang, Miao Zhao, Wei-Nan Zhang, Fuzheng Zhang, Xing Xie, Minyi Guo
The goal of graph representation learning is to embed each vertex in a graph into a low-dimensional vector space.
Ranked #1 on Node Classification on Wikipedia
no code implementations • 28 Feb 2017 • Shanshan Huang, Yichao Xiong, Ya zhang, Jia Wang
Considering the difficulty in obtaining labeled datasets for image retrieval task in large scale, we propose a novel CNN-based unsupervised hashing method, namely Unsupervised Triplet Hashing (UTH).
4 code implementations • 30 May 2012 • Jia Wang, James Cheng
We first improve the existing in-memory algorithm for computing k-truss in networks of moderate size.
Databases