-
europepmc
2026
置信度 0.80
-
europepmc
2026
置信度 0.80
-
europepmc
2026
置信度 0.80
-
europepmc
2026
置信度 0.80
-
europepmc
2026
置信度 0.80
-
europepmc
2026
置信度 0.80
-
europepmc
2025
置信度 0.80
-
europepmc
2026
置信度 0.80
-
europepmc
2026
置信度 0.80
-
europepmc
2025
置信度 0.80
-
europepmc
2026
置信度 0.80
-
europepmc
2025
置信度 0.80
-
europepmc
2026
置信度 0.80
-
europepmc
2026
置信度 0.80
-
europepmc
2025
置信度 0.80
-
europepmc
2026
置信度 0.80
-
europepmc
2025
置信度 0.80
-
europepmc
2025
置信度 0.80
-
europepmc
2025
置信度 0.80
-
europepmc
2025
置信度 0.80
-
europepmc
2025
置信度 0.80
-
europepmc
2025
置信度 0.80
-
europepmc
2025
置信度 0.80
-
crossref
Yichen Liu
2024-12-29T23:02:12Z
置信度 0.70
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crossref
Immanuel Koh, Nuozhi Liu
2024-01-11T13:17:29Z
置信度 0.70
-
We present a dynamic kernel-based deblurring method for Neural Radiance Fields (NeRF), aimed at overcoming the limitations of previous methods that use fixed blur kernels. While prior works successfully address blur caused by camera motion or defocus, they can…
crossref
Shu Chen, Mengze Jia, Peng Chen
2026-01-05T12:27:13Z
置信度 0.70
-
Neural radiance fields with multi-resolution hash encodings have advanced view synthesis, yet their reliance on fixed-resolution grids fundamentally conflicts with the non-uniform structure of natural scenes. This leads to redundant computation in smooth regio…
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Zepeng Yang, Bo Ma
2026-02-23T13:51:37Z
置信度 0.70
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crossref
Haimiao Zhang
2025-01-03T03:28:22Z
置信度 0.70
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crossref
Kang Han, Wei Xiang, Lu Yu
2026-03-02T13:18:04Z
置信度 0.70
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crossref
Ziyang Yan
2025-01-06T19:58:55Z
置信度 0.70
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crossref
Yuan Sun, Wenhua Qian
2024-09-26T22:18:13Z
置信度 0.70
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crossref
Hongjiang Wei
2025-01-26T09:29:57Z
置信度 0.70
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crossref
Yixing Huang
2025-01-13T03:38:22Z
置信度 0.70
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europepmc
2024
置信度 0.80
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crossref
Injae Kim, Minhyuk Choi, Hyunwoo Kim
2026-03-02T13:18:04Z
置信度 0.70
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crossref
Yueqi Duan
2026-01-07T18:32:27Z
置信度 0.70
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crossref
Claudio Manuel López Antypas, Martxel Eizaguirre Ruiz, Aiert Amundarain
2025-05-01T09:08:17Z
置信度 0.70
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crossref
Kirsten W.H. Maas, Thiam-Wai Chua, Daniel Ruijters, Nicola Pezzotti 等
2025-07-16T03:37:36Z
置信度 0.70
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crossref
Hanwen Kang, Kewei Hu, Wei Ying, Yaoqiang Pan 等
2023-11-21T06:47:36Z
置信度 0.70
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We introduce FiReT, a deep learning framework designed for wireless channel estimation and transmitter placement optimization. Accurately modeling channel behavior in complex indoor spaces remains a critical challenge, as conventional approaches rely on exhaus…
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Negar Pouya, Armin Soleymani, Gholamreza Moradi, Farzaneh Abdollahi
2025-10-27T21:50:35Z
置信度 0.70
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crossref
Xinhang Zhang, Daofang Chang, Yanjun Ma, Jiwang Du
2023-12-07T11:21:10Z
置信度 0.70
-
Neural radiance field (NeRF) is a form of deep learning model that may be used to depict 3D scenes from a collection of photos. It has been demonstrated that NeRF can produce photorealistic photographs of fresh perspectives on a scene even from a small number …
crossref
Latika Pinjarkar, Aditya Nittala, Mahantesh P. Mattada, Vedant Pinjarkar 等
2024-11-22T15:40:09Z
置信度 0.70
-
crossref
2011-10-24T18:38:14Z
置信度 0.70
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crossref
Atsuhiro Noguchi, Xiao Sun, Stephen Lin, Tatsuya Harada
2022-02-28T22:08:02Z
置信度 0.70
-
Using the neural radiance field to represent the light field, by editing the light field to obtain a new perspective between sub-aperture images, we can accomplish the super-resolution of the light field in angular domain.
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Yuan Miao, Chang Liu, Di He, Jun Qiu
2023-01-10T17:58:50Z
置信度 0.70
-
Novel view synthesis, a crucial problem in computer graphics with extensive applications, has gained significant attention due to its increasing demand in fields such as autonomous driving, virtual reality, film, and the visual arts. Recent advancements in mac…
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Deng Yu Dong
2024-07-18T06:30:14Z
置信度 0.70
-
crossref
Zhongqi Yang, Yihua Chen, Saru Kumari
2024-01-31T18:31:30Z
置信度 0.70
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europepmc
2025
置信度 0.80
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crossref
Haoyi Gu
2025-07-24T17:51:04Z
置信度 0.70
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crossref
Ruipeng Luo, Qian Guo
2026-06-11T19:58:36Z
置信度 0.70
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Traditional methods for 3D reconstruction of unmanned aerial vehicle (UAV) images often rely on classical multi-view 3D reconstruction techniques. This classical approach involves a sequential process encompassing feature extraction, matching, depth fusion, po…
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Cancheng Jiang, Hua Shao
2023-09-11T08:58:08Z
置信度 0.70
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crossref
Boyuan Zhao
2024-10-01T17:24:02Z
置信度 0.70
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crossref
Junjie Jiang, Hongfeng Xu, Zaixing He, Xinyue Zhao 等
2025-01-27T22:40:31Z
置信度 0.70
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europepmc
2025
置信度 0.80
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crossref
Mangyu Kong, Jaewon Lee, Seongwon Lee, Euntai Kim
2025-09-02T17:28:56Z
置信度 0.70
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crossref
Chibuike Onuoha, Jean Flaherty, Shihao Luo, Truong Thu Huong 等
2024-10-23T17:27:45Z
置信度 0.70
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crossref
Lin Liu, Yuecong Xie, Qiong Huang, Songhua Xu 等
2025-03-05T18:41:16Z
置信度 0.70
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Fast global illumination methods has been one of the most exiting area of rendering because it could solve many industrial problems of achieving balance between realistic rendering and stable frame rate. So this study employs a neural network to learn a radian…
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Ruohan Yang
2023-09-13T06:15:23Z
置信度 0.70
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crossref
Yichen Liu, Benran Hu, Junkai Huang, Yu-Wing Tai 等
2024-01-15T15:55:59Z
置信度 0.70
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europepmc
2025
置信度 0.80
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crossref
Qi Ye
2025-04-17T13:43:39Z
置信度 0.70
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crossref
P Sharmila, S Harish, R Kasiviswanathan, S Maheswaran
2024-06-11T17:32:14Z
置信度 0.70
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crossref
Qian Li, Cheng Wen, Rao Fu
2024-09-30T17:24:16Z
置信度 0.70
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europepmc
2025
置信度 0.80
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crossref
Dustin L. Kelly, Brian S. Thurow
2023-01-21T01:11:41Z
置信度 0.70
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Lidong Guo, Xuefei Ning, Yonggan Fu, Tianchen Zhao 等
2025-11-03T11:20:56Z
置信度 0.70
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crossref
Jianlin Liu, Qiang Nie, Yong Liu, Chengjie Wang
2023-07-04T17:20:56Z
置信度 0.70
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crossref
Yiheng Wang, Shutao Zhang, Ye Xue, Tsung-Hui Chang
2026-07-07T19:42:22Z
置信度 0.70
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crossref
Ling Xu, Yingqian Chai, HanXiang Qin, Herong Wang 等
2024-12-11T19:46:02Z
置信度 0.70
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crossref
Lin Gao
2024-04-03T13:41:52Z
置信度 0.70
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crossref
Lifeng Chen, Jia Liu, Wenquan Sun, Weina Dong 等
2024-07-05T07:01:51Z
置信度 0.70
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crossref
Wei-Cheng Tseng, Hung-Ju Liao, Lin Yen-Chen, Min Sun
2022-07-12T19:36:40Z
置信度 0.70
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crossref
Yicong Peng, Yichao Yan, Shengqi Liu, Yuhao Cheng 等
2026-03-02T13:17:52Z
置信度 0.70
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crossref
Ashish Kumar, Rajagopalan A. N
2025-08-13T17:26:42Z
置信度 0.70
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crossref
Kaito Houjho, Terumasa Aoki
2026-01-29T21:19:25Z
置信度 0.70
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We propose a neural rendering-based 3D reconstruction method for reconstructing the geometry and BRDF of reflective objects from multi-view images captured in unknown environments. Multi-view reconstruction of reflective objects is extremely challenging becaus…
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Lifen Li, Zhengqin Yu, Ronghua Zhang
2024-04-28T02:40:57Z
置信度 0.70
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crossref
Duiping Wu, Yuan Li, Rui Yang, Shenglong Li 等
2024-10-24T17:24:10Z
置信度 0.70
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crossref
Yuanzhen Zhou, Wen Cheng
2023-11-14T12:24:16Z
置信度 0.70
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crossref
Zipei Ding, Zhibin Zhang, Yajie Liang
2024-09-09T17:35:05Z
置信度 0.70
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crossref
Chenyang Wang, Xiaolin Ma, Qinkang Cao, Hailan Kuang 等
2025-06-09T17:33:00Z
置信度 0.70
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crossref
Xinhang Liu, Jiaben Chen, Huai Yu, Yu-Wing Tai 等
2026-03-02T13:17:52Z
置信度 0.70
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crossref
Jianxiong Shen, Ruijie Ren, Adria Ruiz, Francesc Moreno-Noguer
2024-08-08T17:51:05Z
置信度 0.70
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crossref
Qian Li, Cheng Wen, Rao Fu
2024-03-18T18:56:31Z
置信度 0.70
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europepmc
2025
置信度 0.80
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crossref
Yifei Zhang
2025-10-21T17:07:00Z
置信度 0.70
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crossref
Min Wang, Xin Huang, Qing Wang
2025-10-30T17:57:42Z
置信度 0.70
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crossref
Tianjiao Wang, Junxing Yang, Tong Ye, He Huang
2024-12-26T22:14:47Z
置信度 0.70
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crossref
Sadia Mubashshira, Kevin Desai
2025-04-29T17:29:35Z
置信度 0.70
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crossref
Wooseok Kim, Taiki Fukiage, Takeshi Oishi
2024-12-25T19:17:39Z
置信度 0.70
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High-quality green gardens can markedly enhance the quality of life and mental well-being of their users. However, health and lifestyle constraints make it difficult for people to enjoy urban gardens, and traditional methods struggle to offer the high-fidelity…
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Ziyang Li, Yongjian Huai, Qingkuo Meng, Shiquan Dong
2025-08-05T08:46:55Z
置信度 0.70
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europepmc
2025
置信度 0.80
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crossref
2010-11-09T23:30:07Z
置信度 0.70
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crossref
Yuqi Han, Jinli Suo, Qionghao Dai
2023-01-04T18:01:30Z
置信度 0.70
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crossref
Haoyi Zhu
2023-02-06T19:25:41Z
置信度 0.70
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crossref
Takuhiro Kaneko
2024-09-16T17:34:53Z
置信度 0.70
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crossref
Yushuang Wu, Xiao Li, Jinglu Wang, Xiaoguang Han 等
2024-01-15T15:55:59Z
置信度 0.70
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crossref
Zhuohao Gong, Xurong Wang, Wenxin Hu, Qianqian Wang 等
2024-12-17T19:07:41Z
置信度 0.70
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crossref
Ziyun Wu, Jia He, Yan Xing
2025-12-18T18:31:16Z
置信度 0.70
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crossref
2010-11-09T23:30:07Z
置信度 0.70
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crossref
2011-10-24T18:38:14Z
置信度 0.70