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检索条件"机构=Key Laboratory of Technology in Geospatial Information Processing and Application System"
556 条 记 录,以下是251-260 订阅
排序:
Convolutional Neural Network-Based Residue Super-Resolution for Video Coding
Convolutional Neural Network-Based Residue Super-Resolution ...
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IEEE Visual Communications and Image processing (VCIP)
作者: Kang Liu Dong Liu Houqiang Li Feng Wu CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei China
Inspired by the progress of image and video super-resolution (SR) achieved by convolutional neural network (CNN), we propose a CNN-based residue SR method for video coding. Different from the previous works that opera... 详细信息
来源: 评论
End-to-End Facial Image Compression with Integrated Semantic Distortion Metric
End-to-End Facial Image Compression with Integrated Semantic...
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IEEE Visual Communications and Image processing (VCIP)
作者: Tianyu He Zhibo Chen CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China
High efficient facial image compression is broadly required and challenging for surveillance and security scenarios, while either traditional general image codecs or special facial image compression schemes only heuri... 详细信息
来源: 评论
Global Homography Motion Compensation for Versatile Video Coding
Global Homography Motion Compensation for Versatile Video Co...
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IEEE Visual Communications and Image processing (VCIP)
作者: Yao Li Zhuoyuan Li Li Li Dong Liu Houqiang Li CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei China
In Versatile Video Coding (VVC), local affine motion compensation (LAMC) is adopted to handle complex motions, such as rotation and zooming. However, it is inefficient to use LAMC to handle the global motion due to th... 详细信息
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Hybrid transform for HEVC-based lossless coding
Hybrid transform for HEVC-based lossless coding
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IEEE International Symposium on Circuits and systems (ISCAS)
作者: Fangdong Chen Jinlei Zhang Houqiang Li CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China
The High Efficiency Video Coding (HEVC) with the transform bypass mode is simple but inefficient for lossless coding. For this reason, we propose a novel transform to further eliminate the redundancy between residues ... 详细信息
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Deeply Exploit Depth information for Object Detection
Deeply Exploit Depth Information for Object Detection
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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
作者: Saihui Hou Zilei Wang Feng Wu CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China
This paper addresses the issue on how to more effectively coordinate the depth with RGB aiming at boosting the performance of RGB-D object detection. Particularly, we investigate two primary ideas under the CNN model:... 详细信息
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Improving Compression Artifact Reduction via End-to-End Learning of Side information
Improving Compression Artifact Reduction via End-to-End Lear...
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IEEE Visual Communications and Image processing (VCIP)
作者: Haichuan Ma Dong Liu Feng Wu CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei China
We propose to improve neural network-based compression artifact reduction by transmitting side information for the neural network. The side information consists of artifact descriptors that are obtained by analyzing t... 详细信息
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LEARNED SCALABLE IMAGE COMPRESSION WITH BIDIRECTIONAL CONTEXT DISENTANGLEMENT NETWORK
arXiv
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arXiv 2018年
作者: Zhang, Zhizheng Chen, Zhibo Lin, Jianxin Li, Weiping CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China
In this paper, we propose a learned scalable/progressive image compression scheme based on deep neural networks (DNN), named Bidirectional Context Disentanglement Network (BCD-Net). For learning hierarchical represent... 详细信息
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QUERY DIFFICULTY ESTIMATION VIA PSEUDO RELEVANCE FEEDBACK FOR IMAGE SEARCH
QUERY DIFFICULTY ESTIMATION VIA PSEUDO RELEVANCE FEEDBACK FO...
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IEEE International Conference on Multimedia and Expo
作者: Qianghuai Jia Xinmei Tian Tao Mei CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Microsoft Research
Query difficulty estimation (QDE) attempts to automatically predict the performance of the search results returned for a given query. QDE has been widely investigated in text document retrieval for many years. However... 详细信息
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Improving triplet-wise training of convolutional neural network for vehicle re-identification
Improving triplet-wise training of convolutional neural netw...
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IEEE International Conference on Multimedia and Expo (ICME)
作者: Yiheng Zhang Dong Liu Zheng-Jun Zha CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei China
Vehicle re-identification (re-id) plays an important role in the automatic analysis of the drastically increasing urban surveillance videos. Similar to the other image retrieval problems, vehicle re-id suffers from th... 详细信息
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M-LVC: Multiple Frames Prediction for Learned Video Compression
M-LVC: Multiple Frames Prediction for Learned Video Compress...
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Conference on Computer Vision and Pattern Recognition (CVPR)
作者: Jianping Lin Dong Liu Houqiang Li Feng Wu CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei China
We propose an end-to-end learned video compression scheme for low-latency scenarios. Previous methods are limited in using the previous one frame as reference. Our method introduces the usage of the previous multiple ... 详细信息
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