no code implementations • ECCV 2020 • Jingwei Xin, Nannan Wang, Xinrui Jiang, Jie Li, Heng Huang, Xinbo Gao
Lighter model and faster inference are the focus of current single image super-resolution (SISR) research.
no code implementations • 7 Mar 2023 • Jiang Xie, Qiao Deng, Shuyin Xia, Yangzhou Zhao, Guoyin Wang, Xinbo Gao
In recent years, the problem of fuzzy clustering has been widely concerned.
no code implementations • 2 Mar 2023 • Jiang Xie, Shuyin Xia, Guoyin Wang, Xinbo Gao
We construct coarsegrained granular-balls, and then use granular-balls and MST to implement the clustering method based on "large-scale priority", which can greatly avoid the influence of outliers and accelerate the construction process of MST.
no code implementations • 24 Jan 2023 • Xiao He, Mingrui Zhu, Nannan Wang, Xinbo Gao, Heng Yang
To address this issue, we propose a novel font generation approach by learning the Difference between different styles and the Similarity of the same style (DS-Font).
1 code implementation • 30 Dec 2022 • Decheng Liu, Zeyang Zheng, Chunlei Peng, Yukai Wang, Nannan Wang, Xinbo Gao
Face forgery detection plays an important role in personal privacy and social security.
no code implementations • 8 Dec 2022 • Mingrui Zhu, Xiao He, Nannan Wang, Xiaoyu Wang, Xinbo Gao
Our answer is a novel all-to-key attention mechanism: each position of content features is matched to key positions of style features.
no code implementations • 4 Dec 2022 • Qihuang Zhong, Liang Ding, Yibing Zhan, Yu Qiao, Yonggang Wen, Li Shen, Juhua Liu, Baosheng Yu, Bo Du, Yixin Chen, Xinbo Gao, Chunyan Miao, Xiaoou Tang, DaCheng Tao
This technical report briefly describes our JDExplore d-team's Vega v2 submission on the SuperGLUE leaderboard.
no code implementations • 30 Nov 2022 • De Cheng, Haichun Tai, Nannan Wang, Zhen Wang, Xinbo Gao
In this paper, we propose a Neighbour Consistency guided Pseudo Label Refinement (NCPLR) framework, which can be regarded as a transductive form of label propagation under the assumption that the prediction of each example should be similar to its nearest neighbours'.
1 code implementation • NIPS 2022 • De Cheng, Yixiong Ning, Nannan Wang, Xinbo Gao, Heng Yang, Yuxuan Du, Bo Han, Tongliang Liu
We show that the cycle-consistency regularization helps to minimize the volume of the transition matrix T indirectly without exploiting the estimated noisy class posterior, which could further encourage the estimated transition matrix T to converge to its optimal solution.
no code implementations • 30 Oct 2022 • Yu Zheng, Zhangxuan Dang, Chunlei Peng, Chao Yang, Xinbo Gao
In this paper, we propose a MLP-Mixer based multi-view multi-label neural network for network traffic classification.
1 code implementation • 28 Oct 2022 • Yan Zhang, Xiyuan Gao, Qingyan Duan, Jiaxu Leng, Xiao Pu, Xinbo Gao
By stacking various layers of CSA blocks, we propose the Fourier Complex Transformer (FCT) model to learn global contextual information from VHR aerial images following the hierarchical manners.
no code implementations • 21 Oct 2022 • Shuyin Xia, Xiaoyu Lian, Guoyin Wang, Xinbo Gao, Yabin Shao
Most existing fuzzy set methods use points as their input, which is the finest granularity from the perspective of granular computing.
1 code implementation • 18 Oct 2022 • Decheng Liu, Zhan Dang, Chunlei Peng, Yu Zheng, Shuang Li, Nannan Wang, Xinbo Gao
Experiments conducted on publicly available face forgery detection datasets prove the superior performance of the proposed FedForgery.
no code implementations • 6 Oct 2022 • Shuyin Xia, Guoyin Wang, Xinbo Gao, Xiaoli Peng
GBSVM (Granular-ball Support Vector Machine) is an important attempt to use the coarse granularity of a granular-ball as the input to construct a classifier instead of a data point.
no code implementations • 30 Sep 2022 • Zhigang Su, Dawei Zhou, Decheng Liu, Nannan Wang, Zhen Wang, Xinbo Gao
Growing leakage and misuse of visual information raise security and privacy concerns, which promotes the development of information protection.
1 code implementation • 5 Sep 2022 • Pinjun Luo, GuoQiang Xiao, Xinbo Gao, Song Wu
The designed DLKCB can split the deep-wise large kernel convolution into a smaller depth-wise convolution and a depth-wise dilated convolution without introducing massive parameters and computational overhead.
1 code implementation • 25 Jul 2022 • Dawei Zhou, Nannan Wang, Xinbo Gao, Bo Han, Xiaoyu Wang, Yibing Zhan, Tongliang Liu
To alleviate this negative effect, in this paper, we investigate the dependence between outputs of the target model and input adversarial samples from the perspective of information theory, and propose an adversarial defense method.
no code implementations • 25 Jul 2022 • Jingyuan Yang, Jie Li, Leida Li, Xiumei Wang, Yuxuan Ding, Xinbo Gao
In psychology, the \textit{Object-Appraisal-Emotion} model has demonstrated that each individual's emotion is affected by his/her subjective appraisal, which is further formed by the affective memory.
1 code implementation • 12 Jul 2022 • Decheng Liu, Weijie He, Chunlei Peng, Nannan Wang, Jie Li, Xinbo Gao
The multiple branches transformer is employed to explore the inter-correlation between different attributes in similar semantic regions for attribute feature learning.
no code implementations • 5 Jul 2022 • Yukai Wang, Chunlei Peng, Decheng Liu, Nannan Wang, Xinbo Gao
In recent years, with the rapid development of face editing and generation, more and more fake videos are circulating on social media, which has caused extreme public concerns.
no code implementations • CVPR 2022 • De Cheng, Tongliang Liu, Yixiong Ning, Nannan Wang, Bo Han, Gang Niu, Xinbo Gao, Masashi Sugiyama
In label-noise learning, estimating the transition matrix has attracted more and more attention as the matrix plays an important role in building statistically consistent classifiers.
1 code implementation • 30 May 2022 • Jiachen Yang, Zhuo Zhang, Yicheng Gong, Shukun Ma, Xiaolan Guo, Yue Yang, Shuai Xiao, Jiabao Wen, Yang Li, Xinbo Gao, Wen Lu, Qinggang Meng
Data has now become a shortcoming of deep learning.
1 code implementation • 19 Apr 2022 • Yue Zhao, Lingming Zhang, Yang Liu, Deyu Meng, Zhiming Cui, Chenqiang Gao, Xinbo Gao, Chunfeng Lian, Dinggang Shen
The state-of-the-art deep learning-based methods often simply concatenate the raw geometric attributes (i. e., coordinates and normal vectors) of mesh cells to train a single-stream network for automatic intra-oral scanner image segmentation.
no code implementations • 29 Mar 2022 • De Cheng, Yan Li, Dingwen Zhang, Nannan Wang, Xinbo Gao, Jiande Sun
To properly address this problem, we propose a novel density-variational learning framework to improve the robustness of the image dehzing model assisted by a variety of negative hazy images, to better deal with various complex hazy scenarios.
1 code implementation • CVPR 2022 • Hangyu Li, Nannan Wang, Xi Yang, Xiaoyu Wang, Xinbo Gao
In this paper, we learn an Adaptive Confidence Margin (Ada-CM) to fully leverage all unlabeled data for semi-supervised deep facial expression recognition.
no code implementations • 12 Mar 2022 • Lin Qi, Feng Gao, Junyu Dong, Xinbo Gao, Qian Du
Important findings on the use of spatial and spectral information in the autoencoder framework are discussed.
1 code implementation • 4 Mar 2022 • Mingrui Zhu, Yun Yi, Nannan Wang, Xiaoyu Wang, Xinbo Gao
The large discrepancy between the source non-makeup image and the reference makeup image is one of the key challenges in makeup transfer.
no code implementations • 12 Jan 2022 • Shuyin Xia, Xiaochuan Dai, Guoyin Wang, Xinbo Gao, Elisabeth Giem
In addition, this paper first provides the mathematical models for the granular-ball covering.
no code implementations • 10 Jan 2022 • Shuyin Xia, Cheng Wang, Guoyin Wang, Weiping Ding, Xinbo Gao, JianHang Yu, Yujia Zhai, Zizhong Chen
The granular-ball rough set can simultaneously represent Pawlak rough sets, and the neighborhood rough set, so as to realize the unified representation of the two.
no code implementations • CVPR 2022 • Chuandong Liu, Chenqiang Gao, Fangcen Liu, Jiang Liu, Deyu Meng, Xinbo Gao
In the meantime, we design a reliable background mining module and a point cloud filling data augmentation strategy to generate the confident data for iteratively learning with reliable supervision.
no code implementations • 29 Dec 2021 • Shuyin Xia, Xinyu Bai, Guoyin Wang, Deyu Meng, Xinbo Gao, Zizhong Chen, Elisabeth Giem
This paper present a strong data mining method based on rough set, which can realize feature selection, classification and knowledge representation at the same time.
1 code implementation • 16 Nov 2021 • Yuanfei Huang, Jie Li, Yanting Hu, Xinbo Gao, Hua Huang
Recently, deep-learning-based super-resolution methods have achieved excellent performances, but mainly focus on training a single generalized deep network by feeding numerous samples.
no code implementations • 24 Oct 2021 • Jingyuan Yang, Xinbo Gao, Leida Li, Xiumei Wang, Jinshan Ding
Inspired by this, we propose a novel Scene-Object interreLated Visual Emotion Reasoning network (SOLVER) to predict emotions from images.
no code implementations • 15 Oct 2021 • Wei Xia, Quanxue Gao, Ming Yang, Xinbo Gao
Thus, for the OOS nodes, SCAGC can directly calculate their clustering labels.
no code implementations • 29 Sep 2021 • Fangcen Liu, Chenqiang Gao, Fang Chen, Deyu Meng, WangMeng Zuo, Xinbo Gao
We adopt the self-attention mechanism of the transformer to learn the interaction information of image features in a larger range.
no code implementations • 29 Sep 2021 • De Cheng, Jingyu Zhou, Nannan Wang, Xinbo Gao
However, since person Re-Id is an open-set problem, the clustering based methods often leave out lots of outlier instances or group the instances into the wrong clusters, thus they can not make full use of the training samples as a whole.
1 code implementation • 22 Sep 2021 • Yan Li, De Cheng, Jiande Sun, Dingwen Zhang, Nannan Wang, Xinbo Gao
In this paper, we propose a single image dehazing method with an independent Detail Recovery Network (DRN), which considers capturing the details from the input image over a separate network and then integrates them into a coarse dehazed image.
no code implementations • 4 Sep 2021 • Jingyuan Yang, Jie Li, Xiumei Wang, Yuxuan Ding, Xinbo Gao
Then, we design three specific networks, i. e., Global-Net, Semantic-Net and Expression-Net, to extract distinct emotional features from different stimuli simultaneously.
no code implementations • ICCV 2021 • Xinpeng Ding, Nannan Wang, Shiwei Zhang, De Cheng, Xiaomeng Li, Ziyuan Huang, Mingqian Tang, Xinbo Gao
The contrastive objective aims to learn effective representations by contrastive learning, while the caption objective can train a powerful video encoder supervised by texts.
no code implementations • 15 Aug 2021 • Quanxue Gao, Wei Xia, Xinbo Gao, Xiangdong Zhang, Qin Li, DaCheng Tao
Despite the impressive clustering performance and efficiency in characterizing both the relationship between data and cluster structure, existing graph-based multi-view clustering methods still have the following drawbacks.
no code implementations • 29 Jun 2021 • Tianyu Jiang, Quanxue Gao, Xinbo Gao
Specifically, we construct a hidden and tractable large graph by anchor graph for each view and well exploit complementary information embedded in anchor graphs of different views by tensor Schatten p-norm regularizer.
no code implementations • CVPR 2021 • Jingyuan Yang, Jie Li, Leida Li, Xiumei Wang, Xinbo Gao
Visual Emotion Analysis (VEA) has attracted increasing attention recently with the prevalence of sharing images on social networks.
no code implementations • CVPR 2021 • Zheng Hui, Jie Li, Xiumei Wang, Xinbo Gao
Instead of considering iterative strategy, we make the blur kernel predictor trainable in the whole blind SR model, in which AMNet is well-trained.
no code implementations • CVPR 2021 • Lingming Zhang, Yue Zhao, Deyu Meng, Zhiming Cui, Chenqiang Gao, Xinbo Gao, Chunfeng Lian, Dinggang Shen
State-of-the-art methods directly concatenate the raw attributes of 3D inputs, namely coordinates and normal vectors of mesh cells, to train a single-stream network for fully-automated tooth segmentation.
no code implementations • 10 Jun 2021 • Dawei Zhou, Nannan Wang, Xinbo Gao, Bo Han, Jun Yu, Xiaoyu Wang, Tongliang Liu
However, pre-processing methods may suffer from the robustness degradation effect, in which the defense reduces rather than improving the adversarial robustness of a target model in a white-box setting.
no code implementations • 9 Jun 2021 • Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Chunlei Peng, Xinbo Gao
However, given the continuously evolving attacks, models trained on seen types of adversarial examples generally cannot generalize well to unseen types of adversarial examples.
no code implementations • 17 May 2021 • Andrey Ignatov, Andres Romero, Heewon Kim, Radu Timofte, Chiu Man Ho, Zibo Meng, Kyoung Mu Lee, Yuxiang Chen, Yutong Wang, Zeyu Long, Chenhao Wang, Yifei Chen, Boshen Xu, Shuhang Gu, Lixin Duan, Wen Li, Wang Bofei, Zhang Diankai, Zheng Chengjian, Liu Shaoli, Gao Si, Zhang Xiaofeng, Lu Kaidi, Xu Tianyu, Zheng Hui, Xinbo Gao, Xiumei Wang, Jiaming Guo, Xueyi Zhou, Hao Jia, Youliang Yan
Video super-resolution has recently become one of the most important mobile-related problems due to the rise of video communication and streaming services.
no code implementations • ICCV 2021 • Dawei Zhou, Nannan Wang, Chunlei Peng, Xinbo Gao, Xiaoyu Wang, Jun Yu, Tongliang Liu
Then, we train a denoising model to minimize the distances between the adversarial examples and the natural examples in the class activation feature space.
2 code implementations • CVPR 2021 • Tianwei Lin, Zhuoqi Ma, Fu Li, Dongliang He, Xin Li, Errui Ding, Nannan Wang, Jie Li, Xinbo Gao
Inspired by the common painting process of drawing a draft and revising the details, we introduce a novel feed-forward method named Laplacian Pyramid Network (LapStyle).
1 code implementation • 29 Mar 2021 • Yuanfei Huang, Jie Li, Yanting Hu, Xinbo Gao, Hua Huang
Being extremely dependent on iterative estimation of the degradation prior or optimization of the model from scratch, the existing blind super-resolution (SR) methods are generally time-consuming and less effective, as the estimation of degradation proceeds from a blind initialization and lacks interpretable degradation priors.
no code implementations • ICCV 2021 • Ziyu Wei, Xi Yang, Nannan Wang, Xinbo Gao
Visible infrared person re-identification (VI-REID) aims to match pedestrian images between the daytime visible and nighttime infrared camera views.
no code implementations • 1 Jan 2021 • Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Xinbo Gao
Motivated by this observation, we propose a defense framework ADD-Defense, which extracts the invariant information called \textit{perturbation-invariant representation} (PIR) to defend against widespread adversarial examples.
no code implementations • 26 Dec 2020 • Lingming Zhang, Yue Zhao, Deyu Meng, Zhiming Cui, Chenqiang Gao, Xinbo Gao, Chunfeng Lian, Dinggang Shen
State-of-the-art methods directly concatenate the raw attributes of 3D inputs, namely coordinates and normal vectors of mesh cells, to train a single-stream network for fully-automated tooth segmentation.
no code implementations • 3 Dec 2020 • Bo Liu, Ranglei Wu, Xiuli Bi, Bin Xiao, Weisheng Li, Guoyin Wang, Xinbo Gao
The unfixed encoder autonomously learns the image fingerprints that differentiate between the tampered and non-tampered regions, whereas the fixed encoder intentionally provides the direction information that assists the learning and detection of the network.
no code implementations • 31 Oct 2020 • Shuyin Xia, Wenhua Li, Guoyin Wang, Xinbo Gao, Changqing Zhang, Elisabeth Giem
Based on the theorem, we propose the LRA framework for accelerating rough set algorithms.
1 code implementation • 28 Sep 2020 • Yuanfei Huang, Jie Li, Xinbo Gao, Yanting Hu, Wen Lu
To solve them, we propose a purposeful and interpretable detail-fidelity attention network to progressively process these smoothes and details in divide-and-conquer manner, which is a novel and specific prospect of image super-resolution for the purpose on improving the detail fidelity, instead of blindly designing or employing the deep CNNs architectures for merely feature representation in local receptive fields.
no code implementations • 16 Sep 2020 • Zhikang Wang, Lihuo He, Xinbo Gao, Jane Shen
The mask recalibrates the features to amplify the valuable characteristics and diminish the noise.
3 code implementations • 15 Sep 2020 • Kai Zhang, Martin Danelljan, Yawei Li, Radu Timofte, Jie Liu, Jie Tang, Gangshan Wu, Yu Zhu, Xiangyu He, Wenjie Xu, Chenghua Li, Cong Leng, Jian Cheng, Guangyang Wu, Wenyi Wang, Xiaohong Liu, Hengyuan Zhao, Xiangtao Kong, Jingwen He, Yu Qiao, Chao Dong, Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan, Xiaochuan Li, Zhiqiang Lang, Jiangtao Nie, Wei Wei, Lei Zhang, Abdul Muqeet, Jiwon Hwang, Subin Yang, JungHeum Kang, Sung-Ho Bae, Yongwoo Kim, Geun-Woo Jeon, Jun-Ho Choi, Jun-Hyuk Kim, Jong-Seok Lee, Steven Marty, Eric Marty, Dongliang Xiong, Siang Chen, Lin Zha, Jiande Jiang, Xinbo Gao, Wen Lu, Haicheng Wang, Vineeth Bhaskara, Alex Levinshtein, Stavros Tsogkas, Allan Jepson, Xiangzhen Kong, Tongtong Zhao, Shanshan Zhao, Hrishikesh P. S, Densen Puthussery, Jiji C. V, Nan Nan, Shuai Liu, Jie Cai, Zibo Meng, Jiaming Ding, Chiu Man Ho, Xuehui Wang, Qiong Yan, Yuzhi Zhao, Long Chen, Jiangtao Zhang, Xiaotong Luo, Liang Chen, Yanyun Qu, Long Sun, Wenhao Wang, Zhenbing Liu, Rushi Lan, Rao Muhammad Umer, Christian Micheloni
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results.
no code implementations • 3 Sep 2020 • Lei Zhang, Zhenwei He, Yi Yang, Liang Wang, Xinbo Gao
The traditional object retrieval task aims to learn a discriminative feature representation with intra-similarity and inter-dissimilarity, which supposes that the objects in an image are manually or automatically pre-cropped exactly.
no code implementations • 3 Jul 2020 • Xinpeng Ding, Nannan Wang, Xinbo Gao, Jie Li, Xiaoyu Wang, Tongliang Liu
Specifically, we devise a partial segment loss regarded as a loss sampling to learn integral action parts from labeled segments.
Weakly-supervised Temporal Action Localization
Weakly Supervised Temporal Action Localization
no code implementations • 25 Jun 2020 • Zhenxi Zhang, Chunna Tian, Jie Li, Zhusi Zhong, Zhicheng Jiao, Xinbo Gao
Further, we propose a context encoding module to utilize the global predictor from the error map to enhance the feature representation and regularize the networks.
no code implementations • 25 May 2020 • Bing Cao, Nannan Wang, Xinbo Gao, Jie Li, Zhifeng Li
Heterogeneous face recognition (HFR) refers to matching face images acquired from different domains with wide applications in security scenarios.
no code implementations • 3 May 2020 • Kai Zhang, Shuhang Gu, Radu Timofte, Taizhang Shang, Qiuju Dai, Shengchen Zhu, Tong Yang, Yandong Guo, Younghyun Jo, Sejong Yang, Seon Joo Kim, Lin Zha, Jiande Jiang, Xinbo Gao, Wen Lu, Jing Liu, Kwangjin Yoon, Taegyun Jeon, Kazutoshi Akita, Takeru Ooba, Norimichi Ukita, Zhipeng Luo, Yuehan Yao, Zhenyu Xu, Dongliang He, Wenhao Wu, Yukang Ding, Chao Li, Fu Li, Shilei Wen, Jianwei Li, Fuzhi Yang, Huan Yang, Jianlong Fu, Byung-Hoon Kim, JaeHyun Baek, Jong Chul Ye, Yuchen Fan, Thomas S. Huang, Junyeop Lee, Bokyeung Lee, Jungki Min, Gwantae Kim, Kanghyu Lee, Jaihyun Park, Mykola Mykhailych, Haoyu Zhong, Yukai Shi, Xiaojun Yang, Zhijing Yang, Liang Lin, Tongtong Zhao, Jinjia Peng, Huibing Wang, Zhi Jin, Jiahao Wu, Yifu Chen, Chenming Shang, Huanrong Zhang, Jeongki Min, Hrishikesh P. S, Densen Puthussery, Jiji C. V
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results.
no code implementations • 16 Feb 2020 • Jingwei Xin, Nannan Wang, Xinrui Jiang, Jie Li, Xinbo Gao, Zhifeng Li
In the SR processing, we first generated a group of FACs from the input LR face, and then reconstructed the HR face from this group of FACs.
no code implementations • 15 Feb 2020 • Jingwei Xin, Nannan Wang, Jie Li, Xinbo Gao, Zhifeng Li
Current state-of-the-art CNN methods usually treat the VSR problem as a large number of separate multi-frame super-resolution tasks, at which a batch of low resolution (LR) frames is utilized to generate a single high resolution (HR) frame, and running a slide window to select LR frames over the entire video would obtain a series of HR frames.
no code implementations • 13 Feb 2020 • Haosheng Chen, Qiangqiang Wu, Yanjie Liang, Xinbo Gao, Hanzi Wang
To achieve this goal, we present an Adaptive Time-Surface with Linear Time Decay (ATSLTD) event-to-frame conversion algorithm, which asynchronously and effectively warps the spatio-temporal information of asynchronous retinal events to a sequence of ATSLTD frames with clear object contours.
3 code implementations • 7 Feb 2020 • Zheng Hui, Jie Li, Xiumei Wang, Xinbo Gao
Besides, we devise a geometrical alignment constraint item to compensate for the pixel-based distance between prediction features and ground-truth ones.
Ranked #1 on
Facial Inpainting
on FFHQ
1 code implementation • 18 Nov 2019 • Andreas Lugmayr, Martin Danelljan, Radu Timofte, Manuel Fritsche, Shuhang Gu, Kuldeep Purohit, Praveen Kandula, Maitreya Suin, A. N. Rajagopalan, Nam Hyung Joon, Yu Seung Won, Guisik Kim, Dokyeong Kwon, Chih-Chung Hsu, Chia-Hsiang Lin, Yuanfei Huang, Xiaopeng Sun, Wen Lu, Jie Li, Xinbo Gao, Sefi Bell-Kligler
For training, only one set of source input images is therefore provided in the challenge.
2 code implementations • 4 Nov 2019 • Kai Zhang, Shuhang Gu, Radu Timofte, Zheng Hui, Xiumei Wang, Xinbo Gao, Dongliang Xiong, Shuai Liu, Ruipeng Gang, Nan Nan, Chenghua Li, Xueyi Zou, Ning Kang, Zhan Wang, Hang Xu, Chaofeng Wang, Zheng Li, Lin-Lin Wang, Jun Shi, Wenyu Sun, Zhiqiang Lang, Jiangtao Nie, Wei Wei, Lei Zhang, Yazhe Niu, Peijin Zhuo, Xiangzhen Kong, Long Sun, Wenhao Wang
The challenge had 3 tracks.
4 code implementations • 26 Sep 2019 • Zheng Hui, Xinbo Gao, Yunchu Yang, Xiumei Wang
In recent years, single image super-resolution (SISR) methods using deep convolution neural network (CNN) have achieved impressive results.
Ranked #9 on
Image Super-Resolution
on Manga109 - 3x upscaling
1 code implementation • 24 Jul 2019 • Zheng Hui, Jie Li, Xinbo Gao, Xiumei Wang
In this paper, we propose a novel perceptual image super-resolution method that progressively generates visually high-quality results by constructing a stage-wise network.
Ranked #6 on
Image Super-Resolution
on Manga109 - 4x upscaling
no code implementations • 27 Jun 2019 • Ziqi Ren, Jie Li, Xuetong Xue, Xin Li, Fan Yang, Zhicheng Jiao, Xinbo Gao
In addition, we introduce a novel three-stage learning approach which enables the (cognitive) encoder to gradually distill useful knowledge from the paired (visual) encoder during the learning process.
no code implementations • 18 Jun 2019 • Zhenxi Zhang, Jie Li, Zhusi Zhong, Zhicheng Jiao, Xinbo Gao
3D image segmentation is one of the most important and ubiquitous problems in medical image processing.
no code implementations • 17 Jun 2019 • Zhusi Zhong, Jie Li, Zhenxi Zhang, Zhicheng Jiao, Xinbo Gao
We train the deep encoder-decoder for landmark detection, and combine global landmark configuration with local high-resolution feature responses.
no code implementations • 4 Apr 2019 • Cheng Deng, Zhao Li, Xinbo Gao, DaCheng Tao
In this area, extracting effective statistical characteristics from a JPEG image for classification remains a challenge.
no code implementations • 4 Apr 2019 • Cheng Deng, Zhaojia Chen, Xianglong Liu, Xinbo Gao, DaCheng Tao
Given the benefits of its low storage requirements and high retrieval efficiency, hashing has recently received increasing attention.
no code implementations • 3 Apr 2019 • Hao Wang, Cheng Deng, Xinxu Xu, Wei Liu, Xinbo Gao, DaCheng Tao
Previous works mostly focus on a generative approach that takes a highly abstract and sparse sketch as input and then synthesizes the corresponding natural image.
no code implementations • 12 Mar 2019 • Lei Zhang, Xinbo Gao
Domain is referred to as the state of the world at a certain moment.
no code implementations • 19 Dec 2018 • Xiaodan Zhang, Xinbo Gao, Wen Lu, Lihuo He
The former aims to mimic the functions of peripheral vision to encode the holistic information and provide the attended regions.
no code implementations • 28 Sep 2018 • Yanting Hu, Jie Li, Yuanfei Huang, Xinbo Gao
To capture more informative features and maintain long-term information for image super-resolution, we propose a channel-wise and spatial feature modulation (CSFM) network in which a sequence of feature-modulation memory (FMM) modules is cascaded with a densely connected structure to transform low-resolution features to high informative features.
no code implementations • 23 May 2018 • Xi Yang, Xinbo Gao, Bin Song, Nannan Wang, Dong Yang
In this paper, we aim to explore a new search method for images captured with circular fisheye lens, especially the aurora images.
1 code implementation • CVPR 2018 • Chao Li, Cheng Deng, Ning li, Wei Liu, Xinbo Gao, DaCheng Tao
In addition, we harness a self-supervised semantic network to discover high-level semantic information in the form of multi-label annotations.
2 code implementations • CVPR 2018 • Zheng Hui, Xiumei Wang, Xinbo Gao
Recently, deep convolutional neural networks (CNNs) have been demonstrated remarkable progress on single image super-resolution.
Ranked #4 on
Image Super-Resolution
on IXI
no code implementations • 24 Feb 2018 • Yanting Hu, Xinbo Gao, Jie Li, Yuanfei Huang, Hanzi Wang
To improve information flow and to capture sufficient knowledge for reconstructing the high-frequency details, we propose a cascaded multi-scale cross network (CMSC) in which a sequence of subnetworks is cascaded to infer high resolution features in a coarse-to-fine manner.
no code implementations • 28 Nov 2017 • Haoxuan You, Zhicheng Jiao, Haojun Xu, Jie Li, Ying Wang, Xinbo Gao
Generative adversarial network (GAN) has gotten wide re-search interest in the field of deep learning.
no code implementations • ICCV 2017 • Zhenxing Niu, Mo Zhou, Le Wang, Xinbo Gao, Gang Hua
We address the problem of dense visual-semantic embedding that maps not only full sentences and whole images but also phrases within sentences and salient regions within images into a multimodal embedding space.
no code implementations • 8 Jan 2017 • Nannan Wang, Xinbo Gao, Jie Li
The most time-consuming or main computation complexity for exemplar-based face sketch synthesis methods lies in the neighbor selection process.
no code implementations • 1 Jul 2016 • Chunlei Peng, Xinbo Gao, Nannan Wang, Jie Li
An adaptive sparse graphical representation scheme is designed to represent heterogeneous face images, where a Markov networks model is constructed to generate adaptive sparse vectors.
no code implementations • CVPR 2016 • Zhenxing Niu, Mo Zhou, Le Wang, Xinbo Gao, Gang Hua
To address the non-stationary property of aging patterns, age estimation can be cast as an ordinal regression problem.
no code implementations • 25 Mar 2016 • Nannan Wang, Jie Li, Leiyu Sun, Bin Song, Xinbo Gao
In this paper, we proposed a synthesized face sketch recognition framework based on full-reference image quality assessment metrics.
no code implementations • 2 Mar 2015 • Chunlei Peng, Xinbo Gao, Nannan Wang, Jie Li
Heterogeneous face recognition (HFR) refers to matching face images acquired from different sources (i. e., different sensors or different wavelengths) for identification.
no code implementations • 4 Oct 2014 • Nannan Wang, Xinbo Gao, DaCheng Tao, Xuelong. Li
CLM-based methods consist of a shape model and a number of local experts, each of which is utilized to detect a facial feature point.
no code implementations • CVPR 2014 • Zhenxing Niu, Gang Hua, Xinbo Gao, Qi Tian
In such way, we can efficiently leverage the loosely related tags, and build an intermediate level representation for a collection of weakly annotated images.
no code implementations • 1 Sep 2013 • Fei Gao, DaCheng Tao, Xinbo Gao, Xuelong. Li
The proposed BIQA method is one of learning to rank.