no code implementations • 16 Mar 2023 • Qiao Wu, Jiaqi Yang, Kun Sun, Chu'ai Zhang, Yanning Zhang, Mathieu Salzmann
Specifically, we introduce two cycle-consistency strategies for supervision: 1) Self tracking cycles, which leverage labels to help the model converge better in the early stages of training; 2) forward-backward cycles, which strengthen the tracker's robustness to motion variations and the template noise caused by the template update strategy.
no code implementations • 15 Mar 2023 • Congqi Cao, Yizhe WANG, Yue Lu, Xin Zhang, Yanning Zhang
Existing works in this field mainly suffer from two weaknesses: (1) They often neglect the multi-label case and only focus on temporal modeling.
no code implementations • 14 Mar 2023 • Zhaoshuai Qi, Xiaojun Liu, Xiaolin Liu, Jiaqi Yang, Yanning Zhang
As the gold standard for phase retrieval, phase-shifting algorithm (PS) has been widely used in optical interferometry, fringe projection profilometry, etc.
no code implementations • 28 Feb 2023 • Axi Niu, Pei Wang, Yu Zhu, Jinqiu Sun, Qingsen Yan, Yanning Zhang
GRAB consists of the Ghost Module and Channel and Spatial Attention Module (CSAM) to alleviate the generation of redundant features.
1 code implementation • 16 Feb 2023 • Guoqiang Liang, Zhaojie Chen, Zhaoqiang Chen, Shiyu Ji, Yanning Zhang
In all settings, the online class incremental learning (CIL), where incoming samples from data stream can be used only once, is more challenging and can be encountered more frequently in real world.
no code implementations • 14 Feb 2023 • Axi Niu, Kang Zhang, Trung X. Pham, Jinqiu Sun, Yu Zhu, In So Kweon, Yanning Zhang
Diffusion probabilistic models (DPM) have been widely adopted in image-to-image translation to generate high-quality images.
no code implementations • 14 Feb 2023 • Pei Wang, Danna Xue, Yu Zhu, Jinqiu Sun, Qingsen Yan, Sung-Eui Yoon, Yanning Zhang
For general scene deblurring, the feature space of the blurry image and corresponding sharp image under the high-level vision task is closer, which inspires us to rely on other tasks (e. g. classification) to learn a comprehensive prior in severe blur removal cases.
no code implementations • 1 Feb 2023 • Yinghui Xing, Song Wang, Guoqiang Liang, Qingyi Li, Xiuwei Zhang, Shizhou Zhang, Yanning Zhang
Multispectral pedestrian detection is an important task for many around-the-clock applications, since the visible and thermal modalities can provide complementary information especially under low light conditions.
no code implementations • 16 Dec 2022 • Congqi Cao, Xin Zhang, Shizhou Zhang, Peng Wang, Yanning Zhang
To enhance the discriminative power of features, we propose a batch clustering based loss to encourage a clustering branch to generate distinct normal and abnormal clusters based on a batch of data.
no code implementations • 5 Dec 2022 • Bingliang Jiao, Lingqiao Liu, Liying Gao, Guosheng Lin, Ruiqi Wu, Shizhou Zhang, Peng Wang, Yanning Zhang
The key insight of this design is that the cross-attention mechanism in the transformer could be an ideal solution to align the discriminative texture clues from the original image with the canonical view image, which could compensate for the low-quality texture information of the canonical view image.
Domain Generalization
Generalizable Person Re-identification
+1
1 code implementation • ECCV 2022 2022 • Wei Suo, Mengyang Sun, Kai Niu, Yiqi Gao, Peng Wang, Yanning Zhang, Qi Wu
Text-based person search aims to associate pedestrian images with natural language descriptions.
Ranked #2 on
Text based Person Retrieval
on CUHK-PEDES
1 code implementation • 26 Sep 2022 • Chunwei Tian, Yanning Zhang, WangMeng Zuo, Chia-Wen Lin, David Zhang, Yixuan Yuan
To prevent loss of original information, a multi-level enhancement mechanism guides a CNN to achieve a symmetric architecture for promoting expressive ability of HGSRCNN.
1 code implementation • 26 Sep 2022 • Chunwei Tian, Menghua Zheng, WangMeng Zuo, Bob Zhang, Yanning Zhang, David Zhang
In this paper, we propose a multi-stage image denoising CNN with the wavelet transform (MWDCNN) via three stages, i. e., a dynamic convolutional block (DCB), two cascaded wavelet transform and enhancement blocks (WEBs) and a residual block (RB).
1 code implementation • 7 Sep 2022 • Congqi Cao, Yue Lu, Yanning Zhang
For the context recovery stream, we propose a spatiotemporal U-Net which can fully utilize the motion information to predict the future frame.
Ranked #1 on
Anomaly Detection
on Corridor
1 code implementation • 17 Aug 2022 • Yinghui Xing, Qirui Wu, De Cheng, Shizhou Zhang, Guoqiang Liang, Peng Wang, Yanning Zhang
To make the final image feature concentrate more on the target visual concept, a Class-Aware Visual Prompt Tuning (CAVPT) scheme is further proposed in our DPT, where the class-aware visual prompt is generated dynamically by performing the cross attention between text prompts features and image patch token embeddings to encode both the downstream task-related information and visual instance information.
no code implementations • 29 Jul 2022 • Yinghui Xing, Shuyuan Yang, Song Wang, Yan Zhang, Yanning Zhang
Most of the available deep learning-based pan-sharpening methods sharpen the multispectral images through a one-step scheme, which strongly depends on the reconstruction ability of the network.
no code implementations • 18 Jul 2022 • Yinghui Xing, Yan Zhang, Houjun He, Xiuwei Zhang, Yanning Zhang
The process of fusing a high spatial resolution (HR) panchromatic (PAN) image and a low spatial resolution (LR) multispectral (MS) image to obtain an HRMS image is known as pansharpening.
no code implementations • 13 Jul 2022 • Danna Xue, Fei Yang, Pei Wang, Luis Herranz, Jinqiu Sun, Yu Zhu, Yanning Zhang
Accurate semantic segmentation models typically require significant computational resources, inhibiting their use in practical applications.
no code implementations • 11 Jul 2022 • Shaolin Su, Hanhe Lin, Vlad Hosu, Oliver Wiedemann, Jinqiu Sun, Yu Zhu, Hantao Liu, Yanning Zhang, Dietmar Saupe
Computer vision models for image quality assessment (IQA) predict the subjective effect of generic image degradation, such as artefacts, blurs, bad exposure, or colors.
no code implementations • 25 May 2022 • Eduardo Pérez-Pellitero, Sibi Catley-Chandar, Richard Shaw, Aleš Leonardis, Radu Timofte, Zexin Zhang, Cen Liu, Yunbo Peng, Yue Lin, Gaocheng Yu, Jin Zhang, Zhe Ma, Hongbin Wang, Xiangyu Chen, Xintao Wang, Haiwei Wu, Lin Liu, Chao Dong, Jiantao Zhou, Qingsen Yan, Song Zhang, Weiye Chen, Yuhang Liu, Zhen Zhang, Yanning Zhang, Javen Qinfeng Shi, Dong Gong, Dan Zhu, Mengdi Sun, Guannan Chen, Yang Hu, Haowei Li, Baozhu Zou, Zhen Liu, Wenjie Lin, Ting Jiang, Chengzhi Jiang, Xinpeng Li, Mingyan Han, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Juan Marín-Vega, Michael Sloth, Peter Schneider-Kamp, Richard Röttger, Chunyang Li, Long Bao, Gang He, Ziyao Xu, Li Xu, Gen Zhan, Ming Sun, Xing Wen, Junlin Li, Shuang Feng, Fei Lei, Rui Liu, Junxiang Ruan, Tianhong Dai, Wei Li, Zhan Lu, Hengyan Liu, Peian Huang, Guangyu Ren, Yonglin Luo, Chang Liu, Qiang Tu, Fangya Li, Ruipeng Gang, Chenghua Li, Jinjing Li, Sai Ma, Chenming Liu, Yizhen Cao, Steven Tel, Barthelemy Heyrman, Dominique Ginhac, Chul Lee, Gahyeon Kim, Seonghyun Park, An Gia Vien, Truong Thanh Nhat Mai, Howoon Yoon, Tu Vo, Alexander Holston, Sheir Zaheer, Chan Y. Park
The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i. e. solutions can not exceed a given number of operations).
no code implementations • 28 Apr 2022 • Chunwei Tian, Xuanyu Zhang, Jerry Chun-Wei Lin, WangMeng Zuo, Yanning Zhang, Chia-Wen Lin
Second, we present popular architectures for GANs in big and small samples for image applications.
1 code implementation • CVPR 2022 • Cheng Zhang, Shaolin Su, Yu Zhu, Qingsen Yan, Jinqiu Sun, Yanning Zhang
In this paper, to better study an image's potential value that can be explored for restoration, we propose a novel concept, referring to image restoration potential (IRP).
no code implementations • 10 Mar 2022 • Ganglai Wang, Peng Zhang, Lei Xie, Wei Huang, Yufei zha, Yanning Zhang
DeepFake based digital facial forgery is threatening the public media security, especially when lip manipulation has been used in talking face generation, the difficulty of fake video detection is further improved.
no code implementations • 5 Mar 2022 • Junwen Xiong, Peng Zhang, Lei Xie, Wei Huang, Yufei zha, Yanning Zhang
Multi-modal based speech separation has exhibited a specific advantage on isolating the target character in multi-talker noisy environments.
no code implementations • 14 Feb 2022 • Congqi Cao, Xin Zhang, Shizhou Zhang, Peng Wang, Yanning Zhang
For weakly supervised anomaly detection, most existing work is limited to the problem of inadequate video representation due to the inability of modeling long-term contextual information.
no code implementations • 11 Feb 2022 • Axi Niu, Kang Zhang, Chaoning Zhang, Chenshuang Zhang, In So Kweon, Chang D. Yoo, Yanning Zhang
The former works only for a relatively small perturbation 8/255 with the l_\infty constraint, and GradAlign improves it by extending the perturbation size to 16/255 (with the l_\infty constraint) but at the cost of being 3 to 4 times slower.
no code implementations • 6 Jan 2022 • Lu Yang, Lingqiao Liu, Yunlong Wang, Peng Wang, Yanning Zhang
Our discovery is that training with such an adaptive model can better benefit from more training samples.
no code implementations • 15 Nov 2021 • Yue Lu, Congqi Cao, Yanning Zhang
In this paper, we propose a novel distance-based VAD method to take advantage of all the available normal data efficiently and flexibly.
1 code implementation • 24 Oct 2021 • Ning Wang, Yang Gao, Hao Chen, Peng Wang, Zhi Tian, Chunhua Shen, Yanning Zhang
Neural Architecture Search (NAS) has shown great potential in effectively reducing manual effort in network design by automatically discovering optimal architectures.
1 code implementation • 27 Sep 2021 • Shizhou Zhang, Duo Long, Yitao Gao, Liying Gao, Qian Zhang, Kai Niu, Yanning Zhang
Finding target persons in full scene images with a query of text description has important practical applications in intelligent video surveillance. However, different from the real-world scenarios where the bounding boxes are not available, existing text-based person retrieval methods mainly focus on the cross modal matching between the query text descriptions and the gallery of cropped pedestrian images.
1 code implementation • 31 Jul 2021 • Jingxian Sun, Lichao Zhang, Yufei zha, Abel Gonzalez-Garcia, Peng Zhang, Wei Huang, Yanning Zhang
To solve this problem, we propose to distill representations of the TIR modality from the RGB modality with Cross-Modal Distillation (CMD) on a large amount of unlabeled paired RGB-TIR data.
no code implementations • 24 May 2021 • Guoqiang Liang, Yanbing Lv, Shucheng Li, Shizhou Zhang, Yanning Zhang
Specifically, the generator employs a fully convolutional sequence network to extract global representation of a video, and an attention-based network to output normalized importance scores.
no code implementations • 30 Apr 2021 • Lu Yang, Yunlong Wang, Lingqiao Liu, Peng Wang, Lu Chi, Zehuan Yuan, Changhu Wang, Yanning Zhang
In this paper, we propose a new loss based on center predictivity, that is, a sample must be positioned in a location of the feature space such that from it we can roughly predict the location of the center of same-class samples.
no code implementations • 26 Apr 2021 • Aiqing Fang, Xinbo Zhao, Jiaqi Yang, Yanning Zhang
In addition, a dynamic degradation kernel is proposed to improve the robustness of image restoration and fusion.
no code implementations • 20 Mar 2021 • Congqi Cao, Yue Lu, Yifan Zhang, Dongmei Jiang, Yanning Zhang
Inspired from 2D criss-cross attention used in segmentation task, we propose a recurrent 3D criss-cross attention (RCCA-3D) module to model the dense long-range spatiotemporal contextual information in video for action recognition.
no code implementations • 9 Mar 2021 • Lu Yang, Hongbang Liu, Jinghao Zhou, Lingqiao Liu, Lei Zhang, Peng Wang, Yanning Zhang
Learning cross-view consistent feature representation is the key for accurate vehicle Re-identification (ReID), since the visual appearance of vehicles changes significantly under different viewpoints.
no code implementations • 11 Feb 2021 • Rui Li, Xiantuo He, Danna Xue, Shaolin Su, Qing Mao, Yu Zhu, Jinqiu Sun, Yanning Zhang
While the mappings between image and pixel-wise depth are well-studied in current methods, the correlation between image, depth and scene semantics, however, is less considered.
no code implementations • 15 Jan 2021 • Pei Wang, Wei Sun, Qingsen Yan, Axi Niu, Rui Li, Yu Zhu, Jinqiu Sun, Yanning Zhang
To tackle the above problems, we present a deep two-branch network to deal with blurry images via a component divided module, which divides an image into two components based on the representation of blurry degree.
no code implementations • 15 Dec 2020 • Rui Li, Qing Mao, Pei Wang, Xiantuo He, Yu Zhu, Jinqiu Sun, Yanning Zhang
Based on this framework, we enhance the local feature representation by sampling and feeding the point-based features that locate on the semantic edges to an individual Semantic-guided Edge Enhancement module (SEEM), which is specifically designed for promoting depth estimation on the challenging semantic borders.
no code implementations • 3 Dec 2020 • Jiangtao Nie, Lei Zhang, Wei Wei, Zhiqiang Lang, Yanning Zhang
One of the main reason comes from the fact that the predefined degeneration models (e. g. blur in spatial domain) utilized by most HSI SR methods often exist great discrepancy with the real one, which results in these deep models overfit and ultimately degrade their performance on real data.
no code implementations • 3 Dec 2020 • Lei Zhang, Fei Zhou, Wei Wei, Yanning Zhang
To mitigate this problem, we present a novel deep metric meta-generation method that turns to an orthogonal direction, ie, learning to adaptively generate a specific metric for a new FSL task based on the task description (eg, a few labelled samples).
no code implementations • 10 Nov 2020 • Jiaqi Yang, Zhiqiang Huang, Siwen Quan, Qian Zhang, Yanning Zhang, Zhiguo Cao
This paper focuses on developing efficient and robust evaluation metrics for RANSAC hypotheses to achieve accurate 3D rigid registration.
no code implementations • 26 Oct 2020 • Haibo Su, Peng Wang, Lingqiao Liu, Hui Li, Zhen Li, Yanning Zhang
Fashion products typically feature in compositions of a variety of styles at different clothing parts.
no code implementations • 13 Oct 2020 • Congqi Cao, Yajuan Li, Qinyi Lv, Peng Wang, Yanning Zhang
Few-shot learning aims to recognize instances from novel classes with few labeled samples, which has great value in research and application.
no code implementations • 5 Oct 2020 • Aiqing Fang, Xinbo Zhao, Jiaqi Yang, Beibei Qin, Yanning Zhang
Finally, we explore the commonness and characteristics of different image fusion tasks, which provides a research basis for further research on the continuous learning characteristics of human brain in the field of image fusion.
no code implementations • 21 Jul 2020 • Jiaqi Yang, Jiahao Chen, Zhiqiang Huang, Siwen Quan, Yanning Zhang, Zhiguo Cao
We present a simple yet effective method for 3D correspondence grouping.
no code implementations • 17 Jul 2020 • Aiqing Fang, Xinbo Zhao, Jiaqi Yang, Shihao Cao, Yanning Zhang
Firstly, the relationship between human brain cognitive mechanism and image fusion task is analyzed and a physical model is established to simulate human brain cognitive mechanism.
no code implementations • 12 Jul 2020 • Di Xu, Zhen Li, Yanning Zhang, Qi Cao
This paper presents an illumination estimation method for virtual objects in real environment by learning.
no code implementations • 6 Jun 2020 • Linjiang Zhang, Peng Wang, Hui Li, Zhen Li, Chunhua Shen, Yanning Zhang
On the other hand, the 2D attentional based license plate recognizer with an Xception-based CNN encoder is capable of recognizing license plates with different patterns under various scenarios accurately and robustly.
no code implementations • 20 May 2020 • Cheng Zhang, Qingsen Yan, Yu Zhu, Xianjun Li, Jinqiu Sun, Yanning Zhang
Extensive experiments demonstrate the superiority of the proposed network in terms of suppressing the chromatic aberration and noise artifacts in enhancement, especially when the low-light image has severe noise.
no code implementations • 29 Feb 2020 • Congqi Cao, Yanning Zhang
First, we introduce a semantic alignment loss to align the relation statistics of the features from samples that belong to the same category.
no code implementations • 8 Jan 2020 • Dong Gong, Wei Sun, Qinfeng Shi, Anton Van Den Hengel, Yanning Zhang
Most learning-based super-resolution (SR) methods aim to recover high-resolution (HR) image from a given low-resolution (LR) image via learning on LR-HR image pairs.
no code implementations • 23 Dec 2019 • Aiqing Fang, Xinbo Zhao, Yanning Zhang
In order to improve the robustness and contextual awareness of image fusion tasks, we proposed a multi-task auxiliary learning image fusion theory guided by subjective attention.
no code implementations • 23 Dec 2019 • Aiqing Fang, Xinbo Zhao, Jiaqi Yang, Yanning Zhang
The human visual perception system has strong robustness in image fusion.
no code implementations • 18 Dec 2019 • Aiqing Fang, Xinbo Zhao, Jiaqi Yang, Yanning Zhang
The characteristics of feature selection, nonlinear combination and multi-task auxiliary learning mechanism of the human visual perception system play an important role in real-world scenarios, but the research of image fusion theory based on the characteristics of human visual perception is less.
no code implementations • 25 Oct 2019 • Shizhou Zhang, Yifei Yang, Peng Wang, Guoqiang Liang, Xiuwei Zhang, Yanning Zhang
The problem of cross-modality person re-identification has been receiving increasing attention recently, due to its practical significance.
Cross-Modality Person Re-identification
Person Re-Identification
1 code implementation • 14 Aug 2019 • Shizhou Zhang, Qi Zhang, Yifei Yang, Xing Wei, Peng Wang, Bingliang Jiao, Yanning Zhang
Our method can learn a discriminative and compact feature representation for ReID in aerial imagery and can be trained in an end-to-end fashion efficiently.
no code implementations • 5 Jul 2019 • Jiaqi Yang, Ke Xian, Peng Wang, Yanning Zhang
Seeking consistent point-to-point correspondences between 3D rigid data (point clouds, meshes, or depth maps) is a fundamental problem in 3D computer vision.
no code implementations • 29 Jun 2019 • Jiaqi Yang, Siwen Quan, Peng Wang, Yanning Zhang
The outcomes present interesting findings that may shed new light on this community and provide complementary perspectives to existing evaluations on the topic of local geometric feature description.
2 code implementations • CVPR 2020 • Ning Wang, Yang Gao, Hao Chen, Peng Wang, Zhi Tian, Chunhua Shen, Yanning Zhang
The success of deep neural networks relies on significant architecture engineering.
Ranked #124 on
Object Detection
on COCO test-dev
5 code implementations • CVPR 2019 • Qingsen Yan, Dong Gong, Qinfeng Shi, Anton Van Den Hengel, Chunhua Shen, Ian Reid, Yanning Zhang
Ghosting artifacts caused by moving objects or misalignments is a key challenge in high dynamic range (HDR) imaging for dynamic scenes.
1 code implementation • 2 Apr 2019 • Lu Yang, Fan Dang, Peng Wang, Hui Li, Zhen Li, Yanning Zhang
In this work, we propose a simple yet strong approach for scene text recognition.
no code implementations • ICCV 2019 • Peng Wang, Bingliang Jiao, Lu Yang, Yifei Yang, Shizhou Zhang, Wei Wei, Yanning Zhang
It is capable of explicitly detecting discriminative parts for each specific vehicle and significantly outperforms the evaluated baselines and state-of-the-art vehicle ReID approaches.
no code implementations • 24 Mar 2019 • Lei Zhang, Zhiqiang Lang, Peng Wang, Wei Wei, Shengcai Liao, Ling Shao, Yanning Zhang
To address this problem, we propose a pixel-aware deep function-mixture network for SSR, which is composed of a new class of modules, termed function-mixture (FM) blocks.
no code implementations • 12 Oct 2018 • Dong Gong, Mingkui Tan, Qinfeng Shi, Anton Van Den Hengel, Yanning Zhang
Compared to existing methods, MPTV is less sensitive to the choice of the trade-off parameter between data fitting and regularization.
no code implementations • 2 Jul 2018 • Jun-Jie Zhang, Yong Xia, Yanning Zhang
Detection of pulmonary nodules on chest CT is an essential step in the early diagnosis of lung cancer, which is critical for best patient care.
no code implementations • 10 Jun 2018 • Yiqi Yan, Lei Zhang, Jun Li, Wei Wei, Yanning Zhang
Different from traditional hyperspectral super-resolution approaches that focus on improving the spatial resolution, spectral super-resolution aims at producing a high-resolution hyperspectral image from the RGB observation with super-resolution in spectral domain.
no code implementations • 5 Jun 2018 • Lei Zhang, Peng Wang, Chunhua Shen, Lingqiao Liu, Wei Wei, Yanning Zhang, Anton Van Den Hengel
In this study, we revisit this problem from an orthog- onal view, and propose a novel learning strategy to maxi- mize the pixel-wise fitting capacity of a given lightweight network architecture.
1 code implementation • 10 Apr 2018 • Dong Gong, Zhen Zhang, Qinfeng Shi, Anton Van Den Hengel, Chunhua Shen, Yanning Zhang
Extensive experiments on synthetic benchmarks and challenging real-world images demonstrate that the proposed deep optimization method is effective and robust to produce favorable results as well as practical for real-world image deblurring applications.
no code implementations • IEEE 2018 • Tao Lei, Xiaohong Jia, Yanning Zhang, Lifeng He, Hongy-ing Meng, Senior Member, and Asoke K. Nandi, Fellow, IEEE
However, the introduction oflocal spatial information often leads to a high computationalcomplexity, arising out of an iterative calculation of the distancebetween pixels within local spatial neighbors and clusteringcenters.
no code implementations • ICCV 2017 • Dong Gong, Mingkui Tan, Yanning Zhang, Anton Van Den Hengel, Qinfeng Shi
Rather than attempt to identify outliers to the model a priori, we instead propose to sequentially identify inliers, and gradually incorporate them into the estimation process.
no code implementations • 3 Aug 2017 • Lei Zhang, Wei Wei, Qinfeng Shi, Chunhua Shen, Anton Van Den Hengel, Yanning Zhang
The prior for the non-low-rank structure is established based on a mixture of Gaussians which is shown to be flexible enough, and powerful enough, to inform the completion process for a variety of real tensor data.
no code implementations • CVPR 2017 • Dong Gong, Jie Yang, Lingqiao Liu, Yanning Zhang, Ian Reid, Chunhua Shen, Anton Van Den Hengel, Qinfeng Shi
The critical observation underpinning our approach is thus that learning the motion flow instead allows the model to focus on the cause of the blur, irrespective of the image content.
no code implementations • CVPR 2016 • Zhen Zhang, Qinfeng Shi, Julian McAuley, Wei Wei, Yanning Zhang, Anton Van Den Hengel
Feature matching is a key problem in computer vision and pattern recognition.
no code implementations • CVPR 2016 • Dong Gong, Mingkui Tan, Yanning Zhang, Anton Van Den Hengel, Qinfeng Shi
We show here that a subset of the image gradients are adequate to estimate the blur kernel robustly, no matter the gradient image is sparse or not.
no code implementations • CVPR 2016 • Xinchu Shi, Haibin Ling, Weiming Hu, Junliang Xing, Yanning Zhang
Due to its wide range of applications, matching between two graphs has been extensively studied and remains an active topic.
no code implementations • ICCV 2015 • Lei Zhang, Wei Wei, Yanning Zhang, Fei Li, Chunhua Shen, Qinfeng Shi
To reconstruct hyperspectral image (HSI) accurately from a few noisy compressive measurements, we present a novel manifold-structured sparsity prior based hyperspectral compressive sensing (HCS) method in this study.
no code implementations • CVPR 2015 • Lei Zhang, Wei Wei, Yanning Zhang, Chunna Tian, Fei Li
To address this problem, a novel reweighted Laplace prior based hyperspectral compressive sensing method is proposed in this study.
no code implementations • CVPR 2015 • Yu Zhu, Yanning Zhang, Boyan Bonev, Alan L. Yuille
Based on the fact that singular primitive patches are more invariant to the scale change (i. e. have less ambiguity across different scales), we represent the non-singular primitives as compositions of singular ones, each of which is allowed some deformation.
no code implementations • CVPR 2014 • Yu Zhu, Yanning Zhang, Alan L. Yuille
We proposed a deformable patches based method for single image super-resolution.
no code implementations • 17 Dec 2013 • Zhen Zhang, Qinfeng Shi, Yanning Zhang, Chunhua Shen, Anton Van Den Hengel
We show that using Marginal Polytope Diagrams allows the number of constraints to be reduced without loosening the LP relaxations.
no code implementations • CVPR 2013 • Haichao Zhang, David Wipf, Yanning Zhang
This paper presents a robust algorithm for estimating a single latent sharp image given multiple blurry and/or noisy observations.
no code implementations • CVPR 2013 • Rui Yao, Qinfeng Shi, Chunhua Shen, Yanning Zhang, Anton Van Den Hengel
Despite many advances made in the area, deformable targets and partial occlusions continue to represent key problems in visual tracking.