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243 results on '"Jiang, Chengzhi"'

1. Diff-Shadow: Global-guided Diffusion Model for Shadow Removal

Author

Luo, Jinting, Li, Ru, Jiang, Chengzhi, Han, Mingyan, Zhang, Xiaoming, Jiang, Ting, Fan, Haoqiang, and Liu, Shuaicheng

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

We propose Diff-Shadow, a global-guided diffusion model for high-quality shadow removal. Previous transformer-based approaches can utilize global information to relate shadow and non-shadow regions but are limited in their synthesis ability and recover images with obvious boundaries. In contrast, diffusion-based methods can generate better content but ignore global information, resulting in inconsistent illumination. In this work, we combine the advantages of diffusion models and global guidance to realize shadow-free restoration. Specifically, we propose a parallel UNets architecture: 1) the local branch performs the patch-based noise estimation in the diffusion process, and 2) the global branch recovers the low-resolution shadow-free images. A Reweight Cross Attention (RCA) module is designed to integrate global contextural information of non-shadow regions into the local branch. We further design a Global-guided Sampling Strategy (GSS) that mitigates patch boundary issues and ensures consistent illumination across shaded and unshaded regions in the recovered image. Comprehensive experiments on three publicly standard datasets ISTD, ISTD+, and SRD have demonstrated the effectiveness of Diff-Shadow. Compared to state-of-the-art methods, our method achieves a significant improvement in terms of PSNR, increasing from 32.33dB to 33.69dB on the SRD dataset. Codes will be released.

Published
2024

2. Improving Bracket Image Restoration and Enhancement with Flow-guided Alignment and Enhanced Feature Aggregation

Author

Lin, Wenjie, Liu, Zhen, Jiang, Chengzhi, Han, Mingyan, Jiang, Ting, and Liu, Shuaicheng

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In this paper, we address the Bracket Image Restoration and Enhancement (BracketIRE) task using a novel framework, which requires restoring a high-quality high dynamic range (HDR) image from a sequence of noisy, blurred, and low dynamic range (LDR) multi-exposure RAW inputs. To overcome this challenge, we present the IREANet, which improves the multiple exposure alignment and aggregation with a Flow-guide Feature Alignment Module (FFAM) and an Enhanced Feature Aggregation Module (EFAM). Specifically, the proposed FFAM incorporates the inter-frame optical flow as guidance to facilitate the deformable alignment and spatial attention modules for better feature alignment. The EFAM further employs the proposed Enhanced Residual Block (ERB) as a foundational component, wherein a unidirectional recurrent network aggregates the aligned temporal features to better reconstruct the results. To improve model generalization and performance, we additionally employ the Bayer preserving augmentation (BayerAug) strategy to augment the multi-exposure RAW inputs. Our experimental evaluations demonstrate that the proposed IREANet shows state-of-the-art performance compared with previous methods.

Published
2024

3. Stress and Deformation Analysis of Green Prefabricated Slope Surface Protection Structure for Deep and Large Foundation Pit

Author

ZHONG Lichao, MENG Qiang, LUO Xianmin, XU Qianwei, HAN Yufeng, JIANG Chengzhi, and XIE Jinli

Subjects
deep and large foundation pit, slope surface green prefabricated protection structure, stress, deformation, Transportation engineering, TA1001-1280
Abstract

Objective Excavation of deep and big foundation pit destroys the equilibrium state of the original stress field in the soil, leading to ground deformation. Foundation pit deformation can be controlled by adopting GRF (green prefabricated ) surface protection structure with the premises of green environmental protection and high construction efficiency. An in-depth research on stress performance and deformation properties of GRF surface protection structure for deep and large foundation pit is required. Method Relying on the deep and large foundation pit project of Nanning International Airport Comprehensive Transportation Hub, a combination of finite element numerical simulation and on-site measurements is employed to study the stress and deformation law of the GRF surface protection structure for foundation pit top slope and the GRF surface protection structure between retaining piles in foundation pit. Result & Conclusion With the increase in foundation pit excavation depth, the location of the maximum lateral displacement of foundation pit top slope gradually shifts towards slope toe, with a maximum lateral displacement of 8.67 mm. The use of GRF surface protection structure effectively enhances the stability of foundation pit top slope. Anchor rods help transfer part of the load borne by GRE surface layer to the soil layer, thereby reducing deformation and stress GRF surface layer. The spacing between retaining piles has a great influence on soil arching effect. In this project, retaining pile spacing can be increased to around 2.5 m, and soil arching effect is most obvious at 7-8 meters below the pile top.

Published
2024
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5. Disturbance Action of First Excavation on Reinforcement Effect of Later Excavation in layered Tunnels

Author

XU Qianwei, JIANG Chengzhi, YE Yanwei, YU Hangfei, YUAN Fengjie, QIN Zao, and ZHANG Jun

Subjects
tunnel engineering, surrounding rock disturbance, deformation reinforcement, numerical simulation, Transportation engineering, TA1001-1280
Abstract

Objective In the ultra-close layered tunnel construction, the preceding excavated tunnel can cause unpredictable damage to the surrounding rock, which will affect the smooth construction of the following tunnel and increase the difficulties of engineering construction. Therefore, it is necessary to study the effect of the preceding tunnel on the following ones in the layered tunnel construction. Method Based on a tunnel project in Chongqing, a numerical simulation method is used to compare and analyze the stress distribution patterns and deformation characteristics of the surrounding rock caused by the preceding excavation of the lower layer tunnel. According to the stress characteristics and the deformation law of the upper layer tunnel under different working conditions, the relationship between the deformation control effect of the anchor rod reinforcement measures and the weakening effect of the surrounding rock caused by the lower layer tunnel excavation is analyzed. Result & Conclusion The preceding excavation of the lower layer tunnel causes the vault area settlement with a maximum of 4.1mm and the arch bottom area bulging with a maximum of 6.9 mm. According to the variation intensity of the stress distribution and the equivalent plastic strain range of the surrounding rock, the loosening area of the lower layer tunnel surrounding rock is equivalent to a circular range, and the average thickness of the loosening circle is 2.5m. The excavation unloading of the upper layer tunnel will cause the lower layer tunnel upfloating. After the anchor rod reinforcement measures are taken for the surrounding rock in the lower layer tunnel loosening circle,the strength coefficient of the corresponding surrounding rock is reduced to 0.70~0.75.

Published
2024
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6. NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

Author

Pérez-Pellitero, Eduardo, Catley-Chandar, Sibi, Shaw, Richard, Leonardis, Aleš, Timofte, Radu, Zhang, Zexin, Liu, Cen, Peng, Yunbo, Lin, Yue, Yu, Gaocheng, Zhang, Jin, Ma, Zhe, Wang, Hongbin, Chen, Xiangyu, Wang, Xintao, Wu, Haiwei, Liu, Lin, Dong, Chao, Zhou, Jiantao, Yan, Qingsen, Zhang, Song, Chen, Weiye, Liu, Yuhang, Zhang, Zhen, Zhang, Yanning, Shi, Javen Qinfeng, Gong, Dong, Zhu, Dan, Sun, Mengdi, Chen, Guannan, Hu, Yang, Li, Haowei, Zou, Baozhu, Liu, Zhen, Lin, Wenjie, Jiang, Ting, Jiang, Chengzhi, Li, Xinpeng, Han, Mingyan, Fan, Haoqiang, Sun, Jian, Liu, Shuaicheng, Marín-Vega, Juan, Sloth, Michael, Schneider-Kamp, Peter, Röttger, Richard, Li, Chunyang, Bao, Long, He, Gang, Xu, Ziyao, Xu, Li, Zhan, Gen, Sun, Ming, Wen, Xing, Li, Junlin, Li, Jinjing, Li, Chenghua, Gang, Ruipeng, Li, Fangya, Liu, Chenming, Feng, Shuang, Lei, Fei, Liu, Rui, Ruan, Junxiang, Dai, Tianhong, Li, Wei, Lu, Zhan, Liu, Hengyan, Huang, Peian, Ren, Guangyu, Luo, Yonglin, Liu, Chang, Tu, Qiang, Ma, Sai, Cao, Yizhen, Tel, Steven, Heyrman, Barthelemy, Ginhac, Dominique, Lee, Chul, Kim, Gahyeon, Park, Seonghyun, Vien, An Gia, Mai, Truong Thanh Nhat, Yoon, Howoon, Vo, Tu, Holston, Alexander, Zaheer, Sheir, and Park, Chan Y.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022. This manuscript focuses on the competition set-up, datasets, the proposed methods and their results. The challenge aims at estimating an HDR image from multiple respective low dynamic range (LDR) observations, which might suffer from under- or over-exposed regions and different sources of noise. 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). In Track 2, participants are asked to minimize the complexity of their solutions while imposing a constraint on fidelity scores (i.e. solutions are required to obtain a higher fidelity score than the prescribed baseline). Both tracks use the same data and metrics: Fidelity is measured by means of PSNR with respect to a ground-truth HDR image (computed both directly and with a canonical tonemapping operation), while complexity metrics include the number of Multiply-Accumulate (MAC) operations and runtime (in seconds)., Comment: CVPR Workshops 2022. 15 pages, 21 figures, 2 tables

Published
2022

9. IntraLoss: Further Margin via Gradient-Enhancing Term for Deep Face Recognition

Author

Jiang, Chengzhi, Su, Yanzhou, Wang, Wen, Bai, Haiwei, Liu, Haijun, and Cheng, Jian

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Existing classification-based face recognition methods have achieved remarkable progress, introducing large margin into hypersphere manifold to learn discriminative facial representations. However, the feature distribution is ignored. Poor feature distribution will wipe out the performance improvement brought about by margin scheme. Recent studies focus on the unbalanced inter-class distribution and form a equidistributed feature representations by penalizing the angle between identity and its nearest neighbor. But the problem is more than that, we also found the anisotropy of intra-class distribution. In this paper, we propose the `gradient-enhancing term' that concentrates on the distribution characteristics within the class. This method, named IntraLoss, explicitly performs gradient enhancement in the anisotropic region so that the intra-class distribution continues to shrink, resulting in isotropic and more compact intra-class distribution and further margin between identities. The experimental results on LFW, YTF and CFP-FP show that our outperforms state-of-the-art methods by gradient enhancement, demonstrating the superiority of our method. In addition, our method has intuitive geometric interpretation and can be easily combined with existing methods to solve the previously ignored problems.

Published
2021

11. MIPI 2022 Challenge on RGBW Sensor Fusion: Dataset and Report

Author

Yang, Qingyu, Yang, Guang, Jiang, Jun, Li, Chongyi, Feng, Ruicheng, Zhou, Shangchen, Sun, Wenxiu, Zhu, Qingpeng, Loy, Chen Change, Gu, Jinwei, Wang, Zhen, Li, Daoyu, Zhang, Yuzhe, Peng, Lintao, Chang, Xuyang, Zhang, Yinuo, Bian, Liheng, Li, Bing, Huang, Jie, Yao, Mingde, Xu, Ruikang, Zhao, Feng, Liu, Xiaohui, Xu, Rongjian, Zhang, Zhilu, Wu, Xiaohe, Wang, Ruohao, Li, Junyi, Zuo, Wangmeng, Jia, Zhuang, Lee, DongJae, Jiang, Ting, Wu, Qi, Jiang, Chengzhi, Han, Mingyan, Li, Xinpeng, Lin, Wenjie, Li, Youwei, Fan, Haoqiang, Liu, Shuaicheng, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Karlinsky, Leonid, editor, Michaeli, Tomer, editor, and Nishino, Ko, editor

Published
2023
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12. MIPI 2022 Challenge on Quad-Bayer Re-mosaic: Dataset and Report

Author

Yang, Qingyu, Yang, Guang, Jiang, Jun, Li, Chongyi, Feng, Ruicheng, Zhou, Shangchen, Sun, Wenxiu, Zhu, Qingpeng, Loy, Chen Change, Gu, Jinwei, Wang, Zhen, Li, Daoyu, Zhang, Yuzhe, Peng, Lintao, Chang, Xuyang, Zhang, Yinuo, Wu, Yaqi, Wu, Xun, Fan, Zhihao, Xia, Chengjie, Zhang, Feng, Zeng, Haijin, Feng, Kai, Zhao, Yongqiang, Luong, Hiep Quang, Aelterman, Jan, Truong, Anh Minh, Philips, Wilfried, Liu, Xiaohong, Jia, Jun, Sun, Hanchi, Zhai, Guangtao, Xiao, Longan, Xu, Qihang, Jiang, Ting, Wu, Qi, Jiang, Chengzhi, Han, Mingyan, Li, Xinpeng, Lin, Wenjie, Li, Youwei, Fan, Haoqiang, Liu, Shuaicheng, Wu, Rongyuan, Sun, Lingchen, Yi, Qiaosi, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Karlinsky, Leonid, editor, Michaeli, Tomer, editor, and Nishino, Ko, editor

Published
2023
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13. Semantic Segmentation Using Deep Learning to Extract Total Extraocular Muscles and Optic Nerve from Orbital Computed Tomography Images

Author

Zhu, Fubao, Gao, Zhengyuan, Zhao, Chen, Zhu, Zelin, Liu, Yanyun, Tang, Shaojie, Jiang, Chengzhi, Li, Xinhui, Zhao, Min, and Zhou, Weihua

Subjects
Physics - Medical Physics, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Objectives: Precise segmentation of total extraocular muscles (EOM) and optic nerve (ON) is essential to assess anatomical development and progression of thyroid-associated ophthalmopathy (TAO). We aim to develop a semantic segmentation method based on deep learning to extract the total EOM and ON from orbital CT images in patients with suspected TAO. Materials and Methods: A total of 7,879 images obtained from 97 subjects who underwent orbit CT scans due to suspected TAO were enrolled in this study. Eighty-eight patients were randomly selected into the training/validation dataset, and the rest were put into the test dataset. Contours of the total EOM and ON in all the patients were manually delineated by experienced radiologists as the ground truth. A three-dimensional (3D) end-to-end fully convolutional neural network called semantic V-net (SV-net) was developed for our segmentation task. Intersection over Union (IoU) was measured to evaluate the accuracy of the segmentation results, and Pearson correlation analysis was used to evaluate the volumes measured from our segmentation results against those from the ground truth. Results: Our model in the test dataset achieved an overall IoU of 0.8207; the IoU was 0.7599 for the superior rectus muscle, 0.8183 for the lateral rectus muscle, 0.8481 for the medial rectus muscle, 0.8436 for the inferior rectus muscle and 0.8337 for the optic nerve. The volumes measured from our segmentation results agreed well with those from the ground truth (all R>0.98, P<0.0001). Conclusion: The qualitative and quantitative evaluations demonstrate excellent performance of our method in automatically extracting the total EOM and ON and measuring their volumes in orbital CT images. There is a great promise for clinical application to assess these anatomical structures for the diagnosis and prognosis of TAO., Comment: 17 pages, 8 figures

Published
2020
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22. Research on High Reliability Planning Method in Electric Wireless Network

Author

Tang, Zewei, Jiang, Chengzhi, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Liu, Qi, editor, Liu, Xiaodong, editor, Shen, Tao, editor, and Qiu, Xuesong, editor

Published
2021
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23. Identification of two novel QTL for Fusarium head blight resistance in German wheat cultivar Centrum

Author

Ren, Hui, primary, Zhang, Xin, additional, Zhang, Yibo, additional, Zhang, Ziyang, additional, Cheng, Muzi, additional, Zhang, Lu, additional, Zhang, Xiangxue, additional, Li, Chunchun, additional, Duan, Jiangli, additional, Zhang, Chuanliang, additional, Xiang, Mingjie, additional, Liu, Shengjie, additional, Jiang, Chengzhi, additional, Zeng, Qingdong, additional, Wu, Jianhui, additional, Kang, Zhensheng, additional, Yang, Zujun, additional, Li, Chunlian, additional, Huang, Shuo, additional, and Han, Dejun, additional

Published
2024
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24. Karyotyping Dasypyrum breviaristatum chromosomes with multiple oligonucleotide probes reveals the genomic divergence in Dasypyrum

Author

Yu, Zhihui, Wang, Hongjin, Jiang, Wenxi, Jiang, Chengzhi, Yuan, Weiguang, Li, Guangrong, and Yang, Zujun

Subjects
Grasses -- Identification and classification -- Genetic aspects, Chromosomes -- Identification and classification -- Physiological aspects, Karyotyping -- Methods, Oligonucleotides -- Usage, Biological sciences
Abstract

The perennial species Dasypyrum breviaristatum (genome [V.sup.b]) contains many potentially valuable genes for the improvement of common wheat. Construction of a detailed karyotype of D. breviaristatum chromosomes will be useful for the detection of Dasypyrum chromatin in wheat background. We established the standard karyotype of 1[V.sup.b]-7[V.sup.b] chromosomes through nondenaturing fluorescence in situ hybridization (ND-FISH) technique using 28 oligonucleotide probes from the wheat - D. breviaristatum partial amphiploid TDH-2 (AABB[V.sup.b][V.sup.b]) and newly identified wheat - D. breviaristatum disomic translocation and addition lines D2138 (6[V.sup.b]S.2[V.sup.b]L), D2547 (4[V.sup.b]), and D2532 (3[V.sup.b]S.6[V.sup.b]L) by comparative molecular marker analysis. The ND-FISH with multiple oligo probes was conducted on the durum wheat - D. villosum amphiploid TDV-1 and large karyotype differences between D. breviaristatum and D. villosum was revealed. These ND-FISH probes will be valuable for screening the wheat - Dasypyrum derivative lines for chromosome identification, and the newly developed wheat - D. breviaristatum addition lines may broaden the gene pool of wheat breeding. The differences between D. villosum and D. breviaristatum chromosomes revealed by ND-FISH will help us understand evolutionary divergence of repetitive sequences within the genus Dasypyrum. Key words: Dasypyrum breviaristatum, Dasypyrum villosum, oligo probes, chromosome identification, ND-FISH. L'espece perenne Dasypyrum breviaristatum (genome [V.sup.b]) contient plusieurs genes potentiellement utiles pour l'amelioration genetique du ble tendre. La production d'un caryotype detaille des chromosomes du D. breviaristatum sera utile pour detecter la chromatine du Dasypyrum au sein d'un fond genetique de ble. Les auteurs ont etabli un caryotype standard pour les chromosomes 1[V.sup.b]-7[V.sup.b] via hybridation in situ en fluorescence en conditions non-denaturantes (ND-FISH) a l'aide de 28 sondes oligonucleotidiques. Ces analyses ont ete realisees sur la lignee TDH-2, un amphiploide partiel ble - D. breviaristatum (AABB[V.sup.b][V.sup.b]), ainsi que sur des lignees disomiques de translocation et d'addition [D2138 (6[V.sup.b]S.2[V.sup.b]L), D2547 (4[V.sup.b]) et D2532 (3[V.sup.b]S.6[V.sup.b]L)] nouvellement identifiees par analyse avec des marqueurs moleculaires. L'analyse ND-FISH avec de nombreuses sondes a ete realisee sur TDV-1, un amphiploide ble dur - D. villosum, et de grandes differences caryotypiques entre D. breviaristatum et D. villosum ont ete revelees. Ces sondes ND-FISH seront utiles pour l'identification des chromosomes chez des lignees derivees de croisements ble - Dasypyrum. Les lignees d'addition ble - D. breviaristatum nouvellement produites permettront d'elargir l'assise genetique pour l'amelioration genetique du ble. Les differences revelees par analyse ND-FISH entre les chromosomes du D. villosum et du D. breviaristatum aideront a mieux connaitre la divergence evolutive des sequences repetees au sein du genre Dasypyrum. [Traduit par la Redaction] Mots-cles: Dasypyrum breviaristatum, Dasypyrum villosum, sondes oligonucleotidiques, identification des chromosomes, ND-FISH., Introduction The genus Dasypyrum contains two species, namely the annual D. villosum (L.) P. Candargy (2x = 2n = 14) and the perennial D. breviaristatum (L.) Frederiksen (2x = 2n [...]

Published
2021
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25. Data Leakage Prevention System for Smart Grid

Author

Jiang, Chengzhi, Deng, Song, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Tian, Yuan, editor, Ma, Tinghuai, editor, and Khan, Muhammad Khurram, editor

Published
2020
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27. Detecting Online Fake Reviews via Hierarchical Neural Networks and Multivariate Features

Author

Jiang, Chengzhi, Zhang, Xianguo, Jin, Aiyun, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yang, Haiqin, editor, Pasupa, Kitsuchart, editor, Leung, Andrew Chi-Sing, editor, Kwok, James T., editor, Chan, Jonathan H., editor, and King, Irwin, editor

Published
2020
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29. Neural Networks Merging Semantic and Non-semantic Features for Opinion Spam Detection

Author

Jiang, Chengzhi, Zhang, Xianguo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Tang, Jie, editor, Kan, Min-Yen, editor, Zhao, Dongyan, editor, Li, Sujian, editor, and Zan, Hongying, editor

Published
2019
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43. NTIRE 2023 Image Shadow Removal Challenge Report

Author

Vasluianu, Florin-Alexandru, primary, Seizinger, Tim, additional, Timofte, Radu, additional, Cui, Shuhao, additional, Huang, Junshi, additional, Tian, Shuman, additional, Fan, Mingyuan, additional, Zhang, Jiaqi, additional, Zhu, Li, additional, Wei, Xiaoming, additional, Wei, Xiaolin, additional, Luo, Ziwei, additional, Gustafsson, Fredrik K., additional, Zhao, Zheng, additional, Sjölund, Jens, additional, Schön, Thomas B., additional, Dong, Xiaoyi, additional, Zhang, Xi Sheryl, additional, Li, Chenghua, additional, Leng, Cong, additional, Yeo, Woon-Ha, additional, Oh, Wang-Taek, additional, Lee, Yeo-Reum, additional, Ryu, Han-Cheol, additional, Luo, Jinting, additional, Jiang, Chengzhi, additional, Han, Mingyan, additional, Wu, Qi, additional, Lin, Wenjie, additional, Yu, Lei, additional, Li, Xinpeng, additional, Jiang, Ting, additional, Fan, Haoqiang, additional, Liu, Shuaicheng, additional, Xu, Shuning, additional, Song, Binbin, additional, Chen, Xiangyu, additional, Zhang, Shile, additional, Zhou, Jiantao, additional, Zhang, Zhao, additional, Zhao, Suiyi, additional, Zheng, Huan, additional, Gao, Yangcheng, additional, Wei, Yanyan, additional, Wang, Bo, additional, Ren, Jiahuan, additional, Luo, Yan, additional, Kondo, Yuki, additional, Miyata, Riku, additional, Yasue, Fuma, additional, Naruki, Taito, additional, Ukita, Norimichi, additional, Chang, Hua-En, additional, Yang, Hao-Hsiang, additional, Chen, Yi-Chung, additional, Chiang, Yuan-Chun, additional, Huang, Zhi-Kai, additional, Chen, Wei-Ting, additional, Chen, I-Hsiang, additional, Hsieh, Chia-Hsuan, additional, Kuo, Sy-Yen, additional, Xianwei, Li, additional, Fu, Huiyuan, additional, Liu, Chunlin, additional, Ma, Huadong, additional, Fu, Binglan, additional, He, Huiming, additional, Wang, Mengjia, additional, She, Wenxuan, additional, Liu, Yu, additional, Nathan, Sabari, additional, Kansal, Priya, additional, Zhang, Zhongjian, additional, Yang, Huabin, additional, Wang, Yan, additional, Zhang, Yanru, additional, Phutke, Shruti S., additional, Kulkarni, Ashutosh, additional, Khan, MD Raqib, additional, Murala, Subrahmanyam, additional, Vipparthi, Santosh Kumar, additional, Ye, Heng, additional, Liu, Zixi, additional, Yang, Xingyi, additional, Liu, Songhua, additional, Wu, Yinwei, additional, Jing, Yongcheng, additional, Yu, Qianhao, additional, Zheng, Naishan, additional, Huang, Jie, additional, Long, Yuhang, additional, Yao, Mingde, additional, Zhao, Feng, additional, Zhao, Bowen, additional, Ye, Nan, additional, Shen, Ning, additional, Cao, Yanpeng, additional, Xiong, Tong, additional, Xia, Weiran, additional, Li, Dingwen, additional, and Xia, Shuchen, additional

Published
2023
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44. MIPI 2023 Challenge on RGBW Fusion: Methods and Results

Author

Sun, Qianhui, primary, Yang, Qingyu, additional, Li, Chongyi, additional, Zhou, Shangchen, additional, Feng, Ruicheng, additional, Dai, Yuekun, additional, Sun, Wenxiu, additional, Zhu, Qingpeng, additional, Loy, Chen Change, additional, Gu, Jinwei, additional, Yu, Hongyuan, additional, Liu, Yuqing, additional, Yu, Weichen, additional, Ge, Lin, additional, Zhang, Xiaolin, additional, Jia, Qi, additional, Zhang, Heng, additional, Yin, Xuanwu, additional, Zuo, Kunlong, additional, Wu, Qi, additional, Lin, Wenjie, additional, Jiang, Ting, additional, Jiang, Chengzhi, additional, Han, Mingyan, additional, Li, Xinpeng, additional, Luo, Jinting, additional, Yu, Lei, additional, Fan, Haoqiang, additional, Liu, Shuaicheng, additional, Wang, Kunyu, additional, Cao, Chengzhi, additional, Guan, Yuanshen, additional, Xia, Jiyuan, additional, Xu, Ruikang, additional, Yao, Mingde, additional, and Xiong, Zhiwei, additional

Published
2023
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45. MIPI 2023 Challenge on Nighttime Flare Removal: Methods and Results

Author

Dai, Yuekun, primary, Li, Chongyi, additional, Zhou, Shangchen, additional, Feng, Ruicheng, additional, Zhu, Qingpeng, additional, Sun, Qianhui, additional, Sun, Wenxiu, additional, Loy, Chen Change, additional, Gu, Jinwei, additional, Liu, Shuai, additional, Wang, Hao, additional, Feng, Chaoyu, additional, Wang, Luyang, additional, Shao, Guangqi, additional, Zhang, Chenguang, additional, Wang, Xiaotao, additional, Lei, Lei, additional, Zhang, Dafeng, additional, Kong, Xiangyu, additional, Liu, Guanqun, additional, Bai, Mengmeng, additional, Ouyang, Jia, additional, Wang, Xiaobing, additional, Yuan, Jiahui, additional, Li, Xinpeng, additional, Jiang, Chengzhi, additional, Jiang, Ting, additional, Lin, Wenjie, additional, Wu, Qi, additional, Han, Mingyan, additional, Luo, Jinting, additional, Yu, Lei, additional, Fan, Haoqiang, additional, Liu, Shuaicheng, additional, Yan, Bo, additional, Li, Zhuang, additional, Li, Yadong, additional, Wang, Hongbin, additional, Song, Soonyong, additional, Fu, Minghan, additional, Khan, Rayyan Azam, additional, Wu, Fangxiang, additional, Zhang, Zhao, additional, Zhao, Suiyi, additional, Zheng, Huan, additional, Gao, Yangcheng, additional, Wei, Yanyan, additional, Ren, Jiahuan, additional, Wang, Bo, additional, Luo, Yan, additional, Gao, Shuaibo, additional, Wu, Wenhui, additional, Kang, Sicong, additional, Akalwadi, Nikhil, additional, Raichur, Ankit, additional, Patil, Vinod, additional, G, Allabakash, additional, A, Swaroop, additional, Joshi, Amogh, additional, Desai, Chaitra, additional, Tabib, Ramesh Ashok, additional, Patil, Ujwala, additional, Sicheng Li, Uma Mudenagudi, additional, Zhu, Ruoxi, additional, Lian, Jiazheng, additional, Xu, Shusong, additional, Liu, Zihao, additional, Nathan, Sabari, additional, and Kansal, Priya, additional

Published
2023
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46. MIPI 2023 Challenge on RGBW Remosaic: Methods and Results

Author

Sun, Qianhui, primary, Yang, Qingyu, additional, Li, Chongyi, additional, Zhou, Shangchen, additional, Feng, Ruicheng, additional, Dai, Yuekun, additional, Sun, Wenxiu, additional, Zhu, Qingpeng, additional, Loy, Chen Change, additional, Gu, Jinwei, additional, Liu, Yuqing, additional, Yu, Hongyuan, additional, Yu, Weichen, additional, Dong, Zhen, additional, Han, Binnan, additional, Jia, Qi, additional, Yin, Xuanwu, additional, Zuo, Kunlong, additional, Wu, Yaqi, additional, Fan, Zhihao, additional, Meng, Fanqing, additional, Wu, Xun, additional, Zhang, Jiawei, additional, Zhang, Feng, additional, Han, Mingyan, additional, Luo, Jinting, additional, Wu, Qi, additional, Jiang, Ting, additional, Jiang, Chengzhi, additional, Lin, Wenjie, additional, Li, Xinpeng, additional, Yu, Lei, additional, Fan, Haoqiang, additional, and Liu, Shuaicheng, additional

Published
2023
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47. NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results

Author

Li, Yawei, primary, Zhang, Yulun, additional, Timofte, Radu, additional, Van Gool, Luc, additional, Yu, Lei, additional, Li, Youwei, additional, Li, Xinpeng, additional, Jiang, Ting, additional, Wu, Qi, additional, Han, Mingyan, additional, Lin, Wenjie, additional, Jiang, Chengzhi, additional, Luo, Jinting, additional, Fan, Haoqiang, additional, Liu, Shuaicheng, additional, Wang, Yucong, additional, Cai, Minjie, additional, Li, Mingxi, additional, Zhang, Yuhang, additional, Fan, Xian-Jun, additional, Sheng, Yankai, additional, Mao, Yanyu, additional, Zhang, Nihao, additional, Wang, Qian, additional, Zheng, Mingjun, additional, Sun, Long, additional, Pan, Jinshan, additional, Dong, Jiangxin, additional, Tang, Jinhui, additional, Yang, Zhongbao, additional, Wang, Yan, additional, Pan, Erlin, additional, Cai, Qixuan, additional, Dai, Xinan, additional, Zhussip, Magauiya, additional, Kalyazin, Nikolay, additional, Vyal, Dmitry, additional, Zou, Xueyi, additional, Yan, Youliang, additional, Chung, Heaseo, additional, Zhang, Jin, additional, Yu, Gaocheng, additional, Zhang, Feng, additional, Wang, Hongbin, additional, Liao, Bohao, additional, Du, Zhibo, additional, Wu, Yu-Liang, additional, Shi, Gege, additional, Peng, Long, additional, Wang, Yang, additional, Cao, Yang, additional, Zha, Zhengjun, additional, Huang, Zhi-Kai, additional, Chen, Yi-Chung, additional, Chiang, Yuan-Chun, additional, Yang, Hao-Hsiang, additional, Chen, Wei-Ting, additional, Chang, Hua-En, additional, Chen, I-Hsiang, additional, Hsieh, Chia-Hsuan, additional, Kuo, Sy-Yen, additional, Liu, Xin, additional, Pan, Jiahao, additional, Yu, Hongyuan, additional, Yu, Weichen, additional, Ge, Lin, additional, Dong, Jiahua, additional, Zou, Yajun, additional, Wu, Zhuoyuan, additional, Han, Binnan, additional, Zhang, Xiaolin, additional, Zhang, Heng, additional, Yin, Xuanwu, additional, Zuo, Kunlong, additional, Deng, Weijian, additional, Yuan, Hongjie, additional, Lu, Zengtong, additional, Ouyang, Mingyu, additional, Ma, Wenzhuo, additional, Liu, Nian, additional, Zheng, Hanyou, additional, Zhang, Yuantong, additional, Zhang, Junxi, additional, Chen, Zhenzhong, additional, Gendy, Garas, additional, Sabor, Nabil, additional, Hou, Jingchao, additional, He, Guanghui, additional, Zhu, Yurui, additional, Wang, Xi, additional, Fu, Xueyang, additional, Zha, Zheng-Jun, additional, Yin, Daheng, additional, Liu, Mengyang, additional, Chen, Baijun, additional, Li, Ao, additional, Luo, Lei, additional, Jin, Kangjun, additional, Zhu, Ce, additional, Zhang, Xiaoming, additional, Xie, Chengxing, additional, Li, Linze, additional, Meng, Haiteng, additional, Zhang, Tianlin, additional, Li, Tianrui, additional, Zhao, Xiaole, additional, Zhang, Zhao, additional, Li, Baiang, additional, Zheng, Huan, additional, Zhao, Suiyi, additional, Gao, Yangcheng, additional, Ren, Jiahuan, additional, Hu, Kang, additional, Shi, Jingpeng, additional, Wu, Zhijian, additional, Huang, Dingjiang, additional, Zhu, Jinchen, additional, Li, Hui, additional, Xv, Qianru, additional, Liu, Tianle, additional, Weng, Shizhuang, additional, Wu, Gang, additional, Jiang, Junpeng, additional, Liu, Xianming, additional, Jiang, Junjun, additional, Zhang, Mingjian, additional, Hu, Jing, additional, Wu, Chengxu, additional, Fan, Qinrui, additional, Feng, Chengming, additional, Luo, Ziwei, additional, Hu, Shu, additional, Lyu, Siwei, additional, Wu, Xi, additional, and Wang, Xin, additional

Published
2023
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48. NTIRE 2023 Challenge on Image Denoising: Methods and Results

Author

Li, Yawei, primary, Zhang, Yulun, additional, Timofte, Radu, additional, Gool, Luc Van, additional, Tu, Zhijun, additional, Du, Kunpeng, additional, Wang, Hailing, additional, Chen, Hanting, additional, Li, Wei, additional, Wang, Xiaofei, additional, Hu, Jie, additional, Wang, Yunhe, additional, Kong, Xiangyu, additional, Wu, Jinlong, additional, Zhang, Dafeng, additional, Zhang, Jianxing, additional, Liu, Shuai, additional, Bai, Furui, additional, Feng, Chaoyu, additional, Wang, Hao, additional, Zhang, Yuqian, additional, Shao, Guangqi, additional, Wang, Xiaotao, additional, Lei, Lei, additional, Xu, Rongjian, additional, Zhang, Zhilu, additional, Chen, Yunjin, additional, Ren, Dongwei, additional, Zuo, Wangmeng, additional, Wu, Qi, additional, Han, Mingyan, additional, Cheng, Shen, additional, Li, Haipeng, additional, Jiang, Ting, additional, Jiang, Chengzhi, additional, Li, Xinpeng, additional, Luo, Jinting, additional, Lin, Wenjie, additional, Yu, Lei, additional, Fan, Haoqiang, additional, Liu, Shuaicheng, additional, Arora, Aditya, additional, Zamir, Syed Waqas, additional, Vazquez-Corral, Javier, additional, Derpanis, Konstantinos G., additional, Brown, Michael S., additional, Li, Hao, additional, Zhao, Zhihao, additional, Pan, Jinshan, additional, Dong, Jiangxin, additional, Tang, Jinhui, additional, Yang, Bo, additional, Chen, Jingxiang, additional, Li, Chenghua, additional, Zhang, Xi, additional, Zhang, Zhao, additional, Ren, Jiahuan, additional, Ji, Zhicheng, additional, Miao, Kang, additional, Zhao, Suiyi, additional, Zheng, Huan, additional, Wei, YanYan, additional, Liu, Kangliang, additional, Du, Xiangcheng, additional, Liu, Sijie, additional, Zheng, Yingbin, additional, Wu, Xingjiao, additional, Jin, Cheng, additional, Irny, Rajeev, additional, Koundinya, Sriharsha, additional, Kamath, Vighnesh, additional, Khandelwal, Gaurav, additional, Khowaja, Sunder Ali, additional, Yoon, Jiseok, additional, Lee, Ik Hyun, additional, Chen, Shijie, additional, Zhao, Chengqiang, additional, Yang, Huabin, additional, Zhang, Zhongjian, additional, Huang, Junjia, additional, and Zhang, Yanru, additional

Published
2023
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