1 code implementation • 20 Mar 2025 • Han Yuan, Li Zhang, Zheng Ma
Language models (LMs) have exhibited exceptional versatility in reasoning and in-depth financial analysis through their proprietary information processing capabilities.
no code implementations • 16 Mar 2025 • Kanzhi Cheng, Wenpo Song, Jiaxin Fan, Zheng Ma, Qiushi Sun, Fangzhi Xu, Chenyang Yan, Nuo Chen, Jianbing Zhang, Jiajun Chen
Image captioning has been a longstanding challenge in vision-language research.
no code implementations • 25 Jan 2025 • Jiazhen Chen, Sichao Fu, Zheng Ma, Mingbin Feng, Tony S. Wirjanto, Qinmu Peng
Besides, the existing methods primarily focus on anomaly detection in static graphs, and little effort was paid to consider the continuous evolution characteristic of graphs over time (dynamic graphs).
Graph Anomaly Detection
Semi-supervised Anomaly Detection
+1
no code implementations • 21 Jan 2025 • Zhipeng Ma, Bo Nørregaard Jørgensen, Zheng Ma
Public transportation is a major source of greenhouse gas emissions, highlighting the need to improve bus fuel efficiency.
1 code implementation • 24 Nov 2024 • Zheng Ma, Zeping Mao, Ruixue Zhang, Jiazhen Chen, Lei Xin, Paul Shan, Ali Ghodsi, Ming Li
This paper also provides criteria about when DIA data could be used for de novo peptide sequencing and when not to by providing a comparison between DDA and DIA, in both de novo and database search mode.
no code implementations • 11 Oct 2024 • Jiazhen Chen, Sichao Fu, Zhibin Zhang, Zheng Ma, Mingbin Feng, Tony S. Wirjanto, Qinmu Peng
Few-shot graph anomaly detection (GAD) has recently garnered increasing attention, which aims to discern anomalous patterns among abundant unlabeled test nodes under the guidance of a limited number of labeled training nodes.
1 code implementation • 25 Apr 2024 • Zhe Chen, Weiyun Wang, Hao Tian, Shenglong Ye, Zhangwei Gao, Erfei Cui, Wenwen Tong, Kongzhi Hu, Jiapeng Luo, Zheng Ma, Ji Ma, Jiaqi Wang, Xiaoyi Dong, Hang Yan, Hewei Guo, Conghui He, Botian Shi, Zhenjiang Jin, Chao Xu, Bin Wang, Xingjian Wei, Wei Li, Wenjian Zhang, Bo Zhang, Pinlong Cai, Licheng Wen, Xiangchao Yan, Min Dou, Lewei Lu, Xizhou Zhu, Tong Lu, Dahua Lin, Yu Qiao, Jifeng Dai, Wenhai Wang
Compared to both open-source and proprietary models, InternVL 1. 5 shows competitive performance, achieving state-of-the-art results in 8 of 18 benchmarks.
Ranked #6 on
Multiple-choice
on Neptune-Full
no code implementations • 21 Apr 2024 • Enze Jiang, Jishen Peng, Zheng Ma, Xiong-bin Yan
In recent years we have witnessed a growth in mathematics for deep learning, which has been used to solve inverse problems of partial differential equations (PDEs).
no code implementations • 1 Apr 2024 • Nan Zhou, Zheng Ma
In this paper, we put forward a neural network framework to solve the nonlinear hyperbolic systems.
1 code implementation • 23 Mar 2024 • Lingxing Kong, Yougang Chu, Zheng Ma, Jianbing Zhang, Liang He, Jiajun Chen
Relation extraction is a critical task in the field of natural language processing with numerous real-world applications.
no code implementations • 4 Mar 2024 • Zhipeng Ma, Bo Nørregaard Jørgensen, Zheng Ma
However, there is no comprehensive investigation into energy-efficient driving behaviors and strategies.
no code implementations • 18 Feb 2024 • Zheng Ma, Changxin Wang, Yawen Ouyang, Fei Zhao, Jianbing Zhang, ShuJian Huang, Jiajun Chen
If a certain metric has flaws, it will be exploited by the model and reflected in the generated sentences.
no code implementations • 10 Jan 2024 • Balázs András Tolnai, Zheng Ma, Bo Nørregaard Jørgensen
Energy load disaggregation can contribute to balancing power grids by enhancing the effectiveness of demand-side management and promoting electricity-saving behavior through increased consumer awareness.
no code implementations • 9 Jan 2024 • Daniel Anthony Howard, Bo Nørregaard Jørgensen, Zheng Ma
The study successfully identified the cluster with the best performance.
3 code implementations • CVPR 2023 • Jingkang Yang, Wenxuan Peng, Xiangtai Li, Zujin Guo, Liangyu Chen, Bo Li, Zheng Ma, Kaiyang Zhou, Wayne Zhang, Chen Change Loy, Ziwei Liu
PVSG relates to the existing video scene graph generation (VidSGG) problem, which focuses on temporal interactions between humans and objects grounded with bounding boxes in videos.
no code implementations • 8 Nov 2023 • Xiong-bin Yan, Keke Wu, Zhi-Qin John Xu, Zheng Ma
Full-waveform inversion (FWI) is a powerful geophysical imaging technique that infers high-resolution subsurface physical parameters by solving a non-convex optimization problem.
1 code implementation • 15 Oct 2023 • Zheng Ma, Changxin Wang, Bo Huang, Zixuan Zhu, Jianbing Zhang
Several models adopted a non-autoregressive manner to speed up the process.
1 code implementation • 30 Sep 2023 • Fei Zhao, Taotian Pang, Zhen Wu, Zheng Ma, ShuJian Huang, Xinyu Dai
Previous studies have revealed that ICL is sensitive to the selection and the ordering of demonstrations.
1 code implementation • 6 Aug 2023 • Zheng Ma, Mianzhi Pan, Wenhan Wu, Kanzhi Cheng, Jianbing Zhang, ShuJian Huang, Jiajun Chen
Experiments on our proposed datasets demonstrate that popular VLMs underperform in the food domain compared with their performance in the general domain.
1 code implementation • 2 Aug 2023 • Kanzhi Cheng, Zheng Ma, Shi Zong, Jianbing Zhang, Xinyu Dai, Jiajun Chen
Generating visually grounded image captions with specific linguistic styles using unpaired stylistic corpora is a challenging task, especially since we expect stylized captions with a wide variety of stylistic patterns.
1 code implementation • 2 Aug 2023 • Kanzhi Cheng, Wenpo Song, Zheng Ma, Wenhao Zhu, Zixuan Zhu, Jianbing Zhang
Considering that Vision-Language Pre-Training (VLP) models master massive such knowledge from large-scale web-harvested data, it is promising to utilize the generalizability of VLP models to incorporate knowledge into image descriptions.
no code implementations • 28 Jun 2023 • Keke Wu, Xiong-bin Yan, Shi Jin, Zheng Ma
In this paper, we introduce two types of novel Asymptotic-Preserving Convolutional Deep Operator Networks (APCONs) designed to address the multiscale time-dependent linear transport problem.
no code implementations • 3 Apr 2023 • Xiong-bin Yan, Zhi-Qin John Xu, Zheng Ma
To address this issue, this paper proposes an extension to PINNs called Laplace-based fractional physics-informed neural networks (Laplace-fPINNs), which can effectively solve the forward and inverse problems of fractional diffusion equations.
no code implementations • 3 Dec 2022 • Yanxiang Gong, Zhiwei Xie, Guozhen Duan, Zheng Ma, Mei Xie
To address the issue, we propose a global distribution fitting (GDF) method with a penalty term to confine the generated data distribution.
no code implementations • 22 Nov 2022 • Xiong-bin Yan, Zhi-Qin John Xu, Zheng Ma
A large number of numerical experiments demonstrate that the operator learning method proposed in this work can efficiently solve the forward problems and Bayesian inverse problems of the subdiffusion equation.
no code implementations • 18 Oct 2022 • Zheng Ma, Shi Zong, Mianzhi Pan, Jianbing Zhang, ShuJian Huang, Xinyu Dai, Jiajun Chen
In recent years, vision and language pre-training (VLP) models have advanced the state-of-the-art results in a variety of cross-modal downstream tasks.
no code implementations • 13 Aug 2022 • Katrina Chen, Xiuqin Liang, Zheng Ma, Zhibin Zhang
Data imputation is an effective way to handle missing data, which is common in practical applications.
1 code implementation • 27 May 2022 • Guohang Yan, Liu Zhuochun, Chengjie Wang, Chunlei Shi, Pengjin Wei, Xinyu Cai, Tao Ma, Zhizheng Liu, Zebin Zhong, Yuqian Liu, Ming Zhao, Zheng Ma, Yikang Li
To this end, we present OpenCalib, a calibration toolbox that contains a rich set of various sensor calibration methods.
1 code implementation • 7 May 2022 • Yanxiang Gong, Linjie Deng, Shuai Tao, Xinchen Lu, Peicheng Wu, Zhiwei Xie, Zheng Ma, Mei Xie
With CRPD, a unified detection and recognition network with high efficiency is presented as the baseline.
no code implementations • 8 Jul 2021 • Lulu Zhang, Tao Luo, Yaoyu Zhang, Weinan E, Zhi-Qin John Xu, Zheng Ma
In this paper, we propose a a machine learning approach via model-operator-data network (MOD-Net) for solving PDEs.
no code implementations • 25 May 2021 • Tao Luo, Zheng Ma, Zhiwei Wang, Zhi-Qin John Xu, Yaoyu Zhang
frequency in DNN training.
no code implementations • 23 Mar 2021 • Shiyu Tang, Peijun Tang, Yanxiang Gong, Zheng Ma, Mei Xie
It draws class-wise features closer than coarse feature alignment or class-wise feature alignment only, therefore improves the model's performance to a great extent.
1 code implementation • 2 Mar 2021 • Yuenan Hou, Zheng Ma, Chunxiao Liu, Zhe Wang, Chen Change Loy
Channel pruning is broadly recognized as an effective approach to obtain a small compact model through eliminating unimportant channels from a large cumbersome network.
no code implementations • 30 Jan 2021 • Yaoyu Zhang, Tao Luo, Zheng Ma, Zhi-Qin John Xu
Why heavily parameterized neural networks (NNs) do not overfit the data is an important long standing open question.
no code implementations • 6 Dec 2020 • Tao Luo, Zheng Ma, Zhiwei Wang, Zhi-Qin John Xu, Yaoyu Zhang
A supervised learning problem is to find a function in a hypothesis function space given values on isolated data points.
1 code implementation • 15 Oct 2020 • Tao Luo, Zheng Ma, Zhi-Qin John Xu, Yaoyu Zhang
Recent works show an intriguing phenomenon of Frequency Principle (F-Principle) that deep neural networks (DNNs) fit the target function from low to high frequency during the training, which provides insight into the training and generalization behavior of DNNs in complex tasks.
no code implementations • 27 Jul 2020 • Yue Xiao, Yu Ye, Shaocheng Huang, Li Hao, Zheng Ma, Ming Xiao, Shahid Mumtaz
To handle the data explosion in the era of internet of things (IoT), it is of interest to investigate the decentralized network, with the aim at relaxing the burden to central server along with keeping data privacy.
Signal Processing
1 code implementation • 15 Jul 2020 • Tao Luo, Zhi-Qin John Xu, Zheng Ma, Yaoyu Zhang
In this work, inspired by the phase diagram in statistical mechanics, we draw the phase diagram for the two-layer ReLU neural network at the infinite-width limit for a complete characterization of its dynamical regimes and their dependence on hyperparameters related to initialization.
1 code implementation • NeurIPS 2020 • Zheng Ma, Junyu Xuan, Yu Guang Wang, Ming Li, Pietro Lio
Borrowing ideas from physics, we propose a path integral based graph neural networks (PAN) for classification and regression tasks on graphs.
1 code implementation • CVPR 2020 • Yuenan Hou, Zheng Ma, Chunxiao Liu, Tak-Wai Hui, Chen Change Loy
We study the problem of distilling knowledge from a large deep teacher network to a much smaller student network for the task of road marking segmentation.
Ranked #1 on
Semantic Segmentation
on ApolloScape
no code implementations • 3 Mar 2020 • Hao Ge, Xiaoguang Tu, Yanxiang Gong, Mei Xie, Zheng Ma
The interpretability of Convolutional Neural Networks (CNNs) is an important topic in the field of computer vision.
no code implementations • 30 Dec 2019 • Hao Ge, Xiaoguang Tu, Mei Xie, Zheng Ma
We demonstrate that our two-stream architecture is robust to adversarial examples built by currently known attacking algorithms.
no code implementations • 25 Sep 2019 • Yu Guang Wang, Ming Li, Zheng Ma, Guido Montufar, Xiaosheng Zhuang, Yanan Fan
The input of each pooling layer is transformed by the compressive Haar basis of the corresponding clustering.
1 code implementation • ICML 2020 • Yu Guang Wang, Ming Li, Zheng Ma, Guido Montufar, Xiaosheng Zhuang, Yanan Fan
Deep Graph Neural Networks (GNNs) are useful models for graph classification and graph-based regression tasks.
1 code implementation • 17 Sep 2019 • Linjie Deng, Yanxiang Gong, Xinchen Lu, Yi Lin, Zheng Ma, Mei Xie
To achieve high coverage of target boxes, a normal strategy of conventional one-stage anchor-based detectors is to utilize multiple priors at each spatial position, especially in scene text detection tasks.
1 code implementation • 29 Aug 2019 • Linjie Deng, Yanxiang Gong, Xinchen Lu, Xin Yi, Zheng Ma, Mei Xie
Recently, scene text recognition methods based on deep learning have sprung up in computer vision area.
2 code implementations • ICCV 2019 • Yuenan Hou, Zheng Ma, Chunxiao Liu, Chen Change Loy
Training deep models for lane detection is challenging due to the very subtle and sparse supervisory signals inherent in lane annotations.
Ranked #10 on
Lane Detection
on BDD100K val
no code implementations • 10 Jul 2019 • Ming Li, Zheng Ma, Yu Guang Wang, Xiaosheng Zhuang
Graph Neural Networks (GNNs) have become a topic of intense research recently due to their powerful capability in high-dimensional classification and regression tasks for graph-structured data.
1 code implementation • 21 Jun 2019 • Tao Luo, Zheng Ma, Zhi-Qin John Xu, Yaoyu Zhang
Along with fruitful applications of Deep Neural Networks (DNNs) to realistic problems, recently, some empirical studies of DNNs reported a universal phenomenon of Frequency Principle (F-Principle): a DNN tends to learn a target function from low to high frequencies during the training.
1 code implementation • 24 May 2019 • Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, Zheng Ma
It remains a puzzle that why deep neural networks (DNNs), with more parameters than samples, often generalize well.
no code implementations • 19 May 2019 • Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, Zheng Ma
Overall, our work serves as a baseline for the further investigation of the impact of initialization and loss function on the generalization of DNNs, which can potentially guide and improve the training of DNNs in practice.
no code implementations • 24 Apr 2019 • Zheng Ma, Ming Li, Yuguang Wang
In this paper, we propose PAN, a new graph convolution framework that involves every path linking the message sender and receiver with learnable weights depending on the path length, which corresponds to the maximal entropy random walk.
2 code implementations • 22 Mar 2019 • Xiaoguang Tu, Jian Zhao, Zi-Hang Jiang, Yao Luo, Mei Xie, Yang Zhao, Linxiao He, Zheng Ma, Jiashi Feng
3D face reconstruction from a single 2D image is a challenging problem with broad applications.
Ranked #7 on
Face Alignment
on AFLW2000-3D
no code implementations • 25 Feb 2019 • Longfei Ren, Chengjing Wang, Peipei Tang, Zheng Ma
Since sparse unmixing has emerged as a promising approach to hyperspectral unmixing, some spatial-contextual information in the hyperspectral images has been exploited to improve the performance of the unmixing recently.
1 code implementation • 21 Jan 2019 • Yanxiang Gong, Linjie Deng, Zheng Ma, Mei Xie
Recently, methods based on deep learning have dominated the field of text recognition.
3 code implementations • 19 Jan 2019 • Zhi-Qin John Xu, Yaoyu Zhang, Tao Luo, Yanyang Xiao, Zheng Ma
We study the training process of Deep Neural Networks (DNNs) from the Fourier analysis perspective.
no code implementations • 17 Jan 2019 • Xiaoguang Tu, Hengsheng Zhang, Mei Xie, Yao Luo, Yuefei Zhang, Zheng Ma
We propose a CNN framework using sparsely labeled data from the target domain to learn features that are invariant across domains for face anti-spoofing.
1 code implementation • 17 Jan 2019 • Xiaoguang Tu, Jian Zhao, Mei Xie, Guodong Du, Hengsheng Zhang, Jianshu Li, Zheng Ma, Jiashi Feng
Face anti-spoofing (a. k. a presentation attack detection) has drawn growing attention due to the high-security demand in face authentication systems.
Ranked #2 on
Face Anti-Spoofing
on MSU-MFSD
no code implementations • 17 Jan 2019 • Xiaoguang Tu, Hengsheng Zhang, Mei Xie, Yao Luo, Yuefei Zhang, Zheng Ma
Spatio-temporal information is very important to capture the discriminative cues between genuine and fake faces from video sequences.
no code implementations • ICLR 2019 • Sirui Xie, Junning Huang, Lanxin Lei, Chunxiao Liu, Zheng Ma, Wei zhang, Liang Lin
Reinforcement learning agents need exploratory behaviors to escape from local optima.
2 code implementations • 7 Nov 2018 • Yuenan Hou, Zheng Ma, Chunxiao Liu, Chen Change Loy
In this paper, we considerably improve the accuracy and robustness of predictions through heterogeneous auxiliary networks feature mimicking, a new and effective training method that provides us with much richer contextual signals apart from steering direction.
Ranked #1 on
Steering Control
on BDD100K val
1 code implementation • 8 Apr 2018 • Linjie Deng, Yanxiang Gong, Yi Lin, Jingwen Shuai, Xiaoguang Tu, Yuefei Zhang, Zheng Ma, Mei Xie
Previous approaches for scene text detection usually rely on manually defined sliding windows.
Ranked #1 on
Scene Text Detection
on COCO-Text
1 code implementation • 29 May 2017 • Di Kang, Zheng Ma, Antoni B. Chan
The goal of this paper is to evaluate density maps generated by density estimation methods on a variety of crowd analysis tasks, including counting, detection, and tracking.
no code implementations • CVPR 2015 • Zheng Ma, Lei Yu, Antoni B. Chan
For each region, a sliding window (ROI) is passed over the density map to calculate the instance count within each ROI.
no code implementations • CVPR 2013 • Zheng Ma, Antoni B. Chan
Next, the number of people is estimated in a set of overlapping sliding windows on the temporal slice image, using a regression function that maps from local features to a count.