no code implementations • 19 Jul 2016 • Xinxing Wu, Junping Zhang
Concentration inequalities are indispensable tools for studying the generalization capacity of learning models.
no code implementations • 18 Mar 2018 • Juanying Xie, Qi Hou, Yinghuan Shi, Lv Peng, Liping Jing, Fuzhen Zhuang, Junping Zhang, Xiaoyang Tang, Shengquan Xu
We delete those species with only one living environment image from data set, then partition the rest images from living environment into two subsets, one used as test subset, the other as training subset respectively combined with all standard pattern butterfly images or the standard pattern butterfly images with the same species of the images from living environment.
no code implementations • 8 Apr 2018 • Haiping Zhu, Qi Zhou, Junping Zhang, James Z. Wang
The latent vector preserves personalized face features and the age controls facial aging and rejuvenation.
Ranked #1 on Age Estimation on MORPH
no code implementations • 30 Oct 2018 • Yiming Lei, Yukun Tian, Hongming Shan, Junping Zhang, Ge Wang, Mannudeep Kalra
Therefore, CAM and Grad-CAM cannot provide optimal interpretation for lung nodule categorization task in low-dose CT images, in that fine-grained pathological clues like discrete and irregular shape and margins of nodules are capable of enhancing sensitivity and specificity of nodule classification with regards to CNN.
no code implementations • 7 Nov 2018 • Yukun Tian, Yiming Lei, Junping Zhang, James Z. Wang
We propose a novel framework, the Pan-Density Network (PaDNet), for pan-density crowd counting.
3 code implementations • 15 Nov 2018 • Hanqing Chao, Yiwei He, Junping Zhang, Jianfeng Feng
In this paper we present a novel perspective, where a gait is regarded as a set consisting of independent frames.
Ranked #2 on Multiview Gait Recognition on OU-MVLP
no code implementations • 27 May 2019 • Haiping Zhu, Yuheng Zhang, Guohao Li, Junping Zhang, Hongming Shan
This paper proposes an ordinal distribution regression with a global and local convolutional neural network for gait-based age estimation.
no code implementations • 18 Jul 2019 • Yuan Cao, Qiuying Li, Hongming Shan, Zhizhong Huang, Lei Chen, Leiming Ma, Junping Zhang
Precipitation nowcasting, which aims to precisely predict the short-term rainfall intensity of a local region, is gaining increasing attention in the artificial intelligence community.
no code implementations • 15 Oct 2019 • Xiaoyang Xu, Yiqun Liu, Hanqing Chao, Youcheng Luo, Hai Chu, Lei Chen, Junping Zhang, Leiming Ma
To the best of our knowledge, it is the first expert-free models for bias correction.
1 code implementation • 24 Oct 2019 • Haiping Zhu, Zhizhong Huang, Hongming Shan, Junping Zhang
Face aging is of great importance for cross-age recognition and entertainment-related applications.
no code implementations • 13 Apr 2020 • Yiqun Liu, Shouzhen Chen, Lei Chen, Hai Chu, Xiaoyang Xu, Junping Zhang, Leiming Ma
We thus propose an end-to-end deep-learning BCoP model named Spatio-Temporal feature Auto-Selective (STAS) model to select optimal ST regularity from EC via the ST Feature-selective Mechanisms (SFM/TFM).
no code implementations • 7 Aug 2020 • Haiping Zhu, Hongming Shan, Yuheng Zhang, Lingfu Che, Xiaoyang Xu, Junping Zhang, Jianbo Shi, Fei-Yue Wang
We propose a novel ordinal regression approach, termed Convolutional Ordinal Regression Forest or CORF, for image ordinal estimation, which can integrate ordinal regression and differentiable decision trees with a convolutional neural network for obtaining precise and stable global ordinal relationships.
no code implementations • 7 Nov 2020 • Xu Li, Jingjing Huang, Yibo Lyu, Rui Ni, Jiajin Luo, Junping Zhang
For the even sub-carriers in the frequency domain, the signal in the time domain after the IFFT is symmetric.
no code implementations • 7 Dec 2020 • Yiming Lei, Haiping Zhu, Junping Zhang, Hongming Shan
Recently, an unsure data model (UDM) was proposed to incorporate those unsure nodules by formulating this problem as an ordinal regression, showing better performance over traditional binary classification.
2 code implementations • 7 Dec 2020 • Zhizhong Huang, Shouzhen Chen, Junping Zhang, Hongming Shan
Although impressive results have been achieved with conditional generative adversarial networks (cGANs), the existing cGANs-based methods typically use a single network to learn various aging effects between any two different age groups.
2 code implementations • ICLR 2021 • Yuanyuan Yuan, Shuai Wang, Junping Zhang
Given the ever-growing adoption of machine learning as a service (MLaaS), image analysis software on cloud platforms has been exploited by reconstructing private user images from system side channels.
no code implementations • 31 Jan 2021 • Yiming Lei, Hongming Shan, Junping Zhang
In this paper, we propose a Meta Ordinal Weighting Network (MOW-Net) to explicitly align each training sample with a meta ordinal set (MOS) containing a few samples from all classes.
no code implementations • 1 Feb 2021 • Zhizhong Huang, Junping Zhang, Hongming Shan
Although impressive results have been achieved for age progression and regression, there remain two major issues in generative adversarial networks (GANs)-based methods: 1) conditional GANs (cGANs)-based methods can learn various effects between any two age groups in a single model, but are insufficient to characterize some specific patterns due to completely shared convolutions filters; and 2) GANs-based methods can, by utilizing several models to learn effects independently, learn some specific patterns, however, they are cumbersome and require age label in advance.
1 code implementation • 5 Feb 2021 • Hanqing Chao, Kun Wang, Yiwei He, Junping Zhang, Jianfeng Feng
In this paper, we present a novel perspective that utilizes gait as a deep set, which means that a set of gait frames are integrated by a global-local fused deep network inspired by the way our left- and right-hemisphere processes information to learn information that can be used in identification.
1 code implementation • CVPR 2021 • Zhizhong Huang, Junping Zhang, Hongming Shan
We further validate MTLFace on two popular general face recognition datasets, showing competitive performance for face recognition in the wild.
Ranked #1 on Age-Invariant Face Recognition on FG-NET
1 code implementation • 27 Mar 2021 • Yiqun Liu, Yi Zeng, Jian Pu, Hongming Shan, Peiyang He, Junping Zhang
In this work, we propose a self-supervised gait recognition method, termed SelfGait, which takes advantage of the massive, diverse, unlabeled gait data as a pre-training process to improve the representation abilities of spatiotemporal backbones.
no code implementations • 28 Apr 2021 • Jie Chen, Shouzhen Chen, Mingyuan Bai, Jian Pu, Junping Zhang, Junbin Gao
In this paper, we consider the label dependency of graph nodes and propose a decoupling attention mechanism to learn both hard and soft attention.
1 code implementation • 15 May 2021 • Zhizhong Huang, Shouzhen Chen, Junping Zhang, Hongming Shan
Age progression and regression aim to synthesize photorealistic appearance of a given face image with aging and rejuvenation effects, respectively.
no code implementations • 22 Jul 2021 • Mingyuan Bai, S. T. Boris Choy, Junping Zhang, Junbin Gao
In this paper, we propose a neural ODE model for evolutionary subspace clustering to overcome this limitation and a new objective function with subspace self-expressiveness constraint is introduced.
1 code implementation • 24 Aug 2021 • Zhizhong Huang, Junping Zhang, Yi Zhang, Hongming Shan
To better regularize the LDCT denoising model, this paper proposes a novel method, termed DU-GAN, which leverages U-Net based discriminators in the GANs framework to learn both global and local difference between the denoised and normal-dose images in both image and gradient domains.
no code implementations • 27 Sep 2021 • Zhaorun Chen, Binhao Chen, Shenghan Xie, Liang Gong, Chengliang Liu, Zhengfeng Zhang, Junping Zhang
In complex environments with high dimension, training a reinforcement learning (RL) model from scratch often suffers from lengthy and tedious collection of agent-environment interactions.
no code implementations • 10 Oct 2021 • Jian Lin, Zhengfeng Zhang, Junping Zhang, Xiaopeng Li
Prime factorization is a difficult problem with classical computing, whose exponential hardness is the foundation of Rivest-Shamir-Adleman (RSA) cryptography.
1 code implementation • 23 Nov 2021 • Zhizhong Huang, Jie Chen, Junping Zhang, Hongming Shan
The strengths of ProPos are avoidable class collision issue, uniform representations, well-separated clusters, and within-cluster compactness.
Ranked #2 on Image Clustering on ImageNet-10
2 code implementations • 13 Jan 2022 • Jiaqi Gao, Zhizhong Huang, Yiming Lei, Hongming Shan, James Z. Wang, Fei-Yue Wang, Junping Zhang
Specifically, we propose a Deep Rank-consistEnt pyrAmid Model (DREAM), which makes full use of rank consistency across coarse-to-fine pyramid features in latent spaces for enhanced crowd counting with massive unlabeled images.
no code implementations • 30 Jan 2022 • Xianye Ben, Yi Ren, Junping Zhang, Su-Jing Wang, Kidiyo Kpalma, Weixiao Meng, Yong-Jin Liu
Unlike the conventional facial expressions, micro-expressions are involuntary and transient facial expressions capable of revealing the genuine emotions that people attempt to hide.
no code implementations • 15 Mar 2022 • Yiming Lei, Haiping Zhu, Junping Zhang, Hongming Shan
To improve model generalization with ordinal information, we propose a novel meta ordinal regression forest (MORF) method for medical image classification with ordinal labels, which learns the ordinal relationship through the combination of convolutional neural network and differential forest in a meta-learning framework.
1 code implementation • 19 Mar 2022 • Jie Chen, Shouzhen Chen, Junbin Gao, Zengfeng Huang, Junping Zhang, Jian Pu
Moreover, we propose a simple yet effective Conv-Agnostic GNN framework (CAGNNs) to enhance the performance of most GNNs on heterophily datasets by learning the neighbor effect for each node.
no code implementations • 6 May 2022 • Jiaqi Gao, Jingqi Li, Hongming Shan, Yanyun Qu, James Z. Wang, Fei-Yue Wang, Junping Zhang
Crowd counting has important applications in public safety and pandemic control.
1 code implementation • 9 May 2022 • Weiyi Yu, Zhizhong Huang, Junping Zhang, Hongming Shan
To tackle this issue, we introduce a self-adaptive normalization network, termed SAN-Net, to achieve adaptive generalization on unseen sites for stroke lesion segmentation.
no code implementations • 30 May 2022 • Jie Chen, Weiqi Liu, Zhizhong Huang, Junbin Gao, Junping Zhang, Jian Pu
The performance of GNNs degrades as they become deeper due to the over-smoothing.
Ranked #9 on Node Classification on Squirrel
1 code implementation • 24 Jul 2022 • Zilong Li, Qi Gao, Yaping Wu, Chuang Niu, Junping Zhang, Meiyun Wang, Ge Wang, Hongming Shan
Here we extend the state-of-the-art dual-domain deep network approach into a quad-domain counterpart so that all the features in the sinogram, image, and their corresponding Fourier domains are synergized to eliminate metal artifacts optimally without compromising structural subtleties.
no code implementations • 17 Oct 2022 • Zhizhong Huang, Junping Zhang, Hongming Shan
Extensive experimental results on five benchmark cross-age datasets demonstrate that MTLFace yields superior performance for both AIFR and FAS.
1 code implementation • 18 Oct 2022 • Jie Chen, Shouzhen Chen, Mingyuan Bai, Junbin Gao, Junping Zhang, Jian Pu
Then, we introduce a novel structure-mixing knowledge distillation strategy to enhance the learning ability of MLPs for structure information.
no code implementations • 21 Oct 2022 • Jingqi Li, Jiaqi Gao, Yuzhen Zhang, Hongming Shan, Junping Zhang
Specifically, we first extract the motion features from the encoded motion sequences in the shallow layer.
no code implementations • 4 Nov 2022 • Yin Zhu, Qiuqiang Kong, Junjie Shi, Shilei Liu, Xuzhou Ye, Ju-Chiang Wang, Junping Zhang
Binaural rendering of ambisonic signals is of broad interest to virtual reality and immersive media.
1 code implementation • CVPR 2023 • Jie Chen, Zilong Li, Yin Zhu, Junping Zhang, Jian Pu
We design a simple yet effective HopGNN framework that can easily utilize existing GNNs to achieve hop interaction.
no code implementations • 15 Jan 2023 • Yiming Lei, Zilong Li, Yangyang Li, Junping Zhang, Hongming Shan
However, the manifold of the resultant feature representations does not maintain the intrinsic ordinal relations of interest, which hinders the effectiveness of the image ordinal estimation.
1 code implementation • CVPR 2023 • Zhizhong Huang, Junping Zhang, Hongming Shan
In this paper, we present TCL, a novel twin contrastive learning model to learn robust representations and handle noisy labels for classification.
Ranked #19 on Image Classification on mini WebVision 1.0
1 code implementation • 16 Mar 2023 • Mingliang Dai, Zhizhong Huang, Jiaqi Gao, Hongming Shan, Junping Zhang
To alleviate the negative impact of noisy annotations, we propose a novel crowd counting model with one convolution head and one transformer head, in which these two heads can supervise each other in noisy areas, called Cross-Head Supervision.
1 code implementation • 4 Apr 2023 • Qi Gao, Zilong Li, Junping Zhang, Yi Zhang, Hongming Shan
First, CoreDiff utilizes LDCT images to displace the random Gaussian noise and employs a novel mean-preserving degradation operator to mimic the physical process of CT degradation, significantly reducing sampling steps thanks to the informative LDCT images as the starting point of the sampling process.
no code implementations • 17 Apr 2023 • Yiming Lei, Zilong Li, Yan Shen, Junping Zhang, Hongming Shan
Drawing on the capability of the contrastive language-image pre-training (CLIP) model to learn generalized visual representations from text annotations, in this paper, we propose CLIP-Lung, a textual knowledge-guided framework for lung nodule malignancy prediction.
1 code implementation • 12 Jul 2023 • Chenglong Ma, Zilong Li, Junping Zhang, Yi Zhang, Hongming Shan
Specifically, we first propose a frequency-band-aware artifact modeling network (FreeNet), which learns artifact-related frequency-band attention in Fourier domain for better modeling the globally distributed streak artifact on the sparse-view CT images.
1 code implementation • ICCV 2023 • Zhizhong Huang, Siteng Ma, Junping Zhang, Hongming Shan
This paper proposes a novel adaptive nonlinear latent transformation for disentangled and conditional face editing, termed AdaTrans.
1 code implementation • ICCV 2023 • Yujie Wei, Jiaxin Ye, Zhizhong Huang, Junping Zhang, Hongming Shan
Online continual learning (CL) studies the problem of learning continuously from a single-pass data stream while adapting to new data and mitigating catastrophic forgetting.
1 code implementation • ICCV 2023 • Zilong Li, Chenglong Ma, Jie Chen, Junping Zhang, Hongming Shan
The reconstructed images, however, suffer from strong artifacts, greatly limiting their diagnostic value.
1 code implementation • 11 Sep 2023 • Binglei Li, Zhizhong Huang, Hongming Shan, Junping Zhang
Specifically, SDFlow decomposes the original latent code into different irrelevant variables by jointly optimizing two components: (i) a semantic encoder to estimate semantic variables from input faces and (ii) a flow-based transformation module to map the latent code into a semantic-irrelevant variable in Gaussian distribution, conditioned on the learned semantic variables.
no code implementations • 20 Nov 2023 • Xin Zheng, Ziang Peng, Yuan Cao, Hongming Shan, Junping Zhang
Video prediction aims to predict future frames from a video's previous content.
1 code implementation • 21 Nov 2023 • Zhizhong Huang, Mingliang Dai, Yi Zhang, Junping Zhang, Hongming Shan
In this paper, we propose a generalized framework for both few-shot and zero-shot object counting based on detection.
1 code implementation • 8 Dec 2023 • Zilong Li, Yiming Lei, Chenglong Ma, Junping Zhang, Hongming Shan
Second, we devise a novel prompt-to-prompt interaction module to fuse these two prompts into a universal restoration prompt.
1 code implementation • 13 Dec 2023 • Chenglong Ma, Zilong Li, Junjun He, Junping Zhang, Yi Zhang, Hongming Shan
To enjoy the multi-setting synergy in a single model, we propose a novel Prompted Contextual Transformer (ProCT) for incomplete-view CT reconstruction.
1 code implementation • 19 Jan 2024 • Chenhui Wang, Yiming Lei, Tao Chen, Junping Zhang, Yuxin Li, Hongming Shan
Inspired by that various longitudinal biomarkers and cognitive measurements present an ordinal pathway on AD progression, we propose a novel Hybrid-granularity Ordinal PrototypE learning (HOPE) method to characterize AD ordinal progression for MCI progression prediction.