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检索条件"机构=Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems"
527 条 记 录,以下是181-190 订阅
排序:
Objective quality assessment for image retargeting based on hybrid distortion pooled model
Objective quality assessment for image retargeting based on ...
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International Workshop on Quality of Multimedia Experience, QoMEx
作者: Jianxin Lin Lingling Zhu Zhibo Chen Xiaoming Chen CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China
With the increasing popularity of mobile devices, there are more and more screens with heterogeneous resolutions. In order to solve the mismatching problem of images displaying on different screens, various image reta... 详细信息
来源: 评论
SEAMLESS SWITCHING OF H.265/HEVC-CODED DASH REPRESENTATIONS WITH OPEN GOP PREDICTION STRUCTURE
SEAMLESS SWITCHING OF H.265/HEVC-CODED DASH REPRESENTATIONS ...
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IEEE International Conference on Image processing
作者: Ye Yan Miska M. Hannuksela Houqiang Li CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Nokia Technologies
The Dynamic Adaptive Streaming over HTTP (DASH) enables bitrate adaptation through different representations of the same content. It is common to encode random access point (RAP) pictures at segment boundaries to supp... 详细信息
来源: 评论
3D-HEVC visual quality assessment: Database and bitstream model
3D-HEVC visual quality assessment: Database and bitstream mo...
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International Workshop on Quality of Multimedia Experience, QoMEx
作者: Wei Zhou Ning Liao Zhibo Chen Weiping Li CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China
Visual Quality Assessment of 3D/stereoscopic video (3D VQA) is significant for both quality monitoring and optimization of the existing 3D video services. In this paper, we build a 3D video database based on the lates... 详细信息
来源: 评论
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
来源: 评论
Chain Code-Based Occupancy Map Coding for Video-Based Point Cloud Compression
Chain Code-Based Occupancy Map Coding for Video-Based Point ...
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IEEE Visual Communications and Image processing (VCIP)
作者: Runyu Yang Ning Yan Li Li 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
In video-based point cloud compression (V-PCC), occupancy map video is utilized to indicate whether a 2-D pixel corresponds to a valid 3-D point or not. In the current design of V-PCC, the occupancy map video is direc... 详细信息
来源: 评论
Light Field Compression Based on Implicit Neural Representation
Light Field Compression Based on Implicit Neural Representat...
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Picture Coding Symposium, PCS
作者: Henan Wang Hanxin Zhu Zhibo Chen CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China
Light field, as a new data representation format in multimedia, has the ability to capture both intensity and direction of light rays. However, the additional angular information also brings a large volume of data. Cl... 详细信息
来源: 评论
Light Field Compression Based on Implicit Neural Representation
arXiv
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arXiv 2024年
作者: Wang, Henan Zhu, Hanxin Chen, Zhibo CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China
Light field, as a new data representation format in multimedia, has the ability to capture both intensity and direction of light rays. However, the additional angular information also brings a large volume of data. Cl... 详细信息
来源: 评论
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
来源: 评论
Fast genetic multi-operator image retargeting
Fast genetic multi-operator image retargeting
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IEEE Visual Communications and Image processing (VCIP)
作者: Lingling Zhu Zhibo Chen CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China
Content-aware image retargeting has attracted substantial research interests in the related research community. However, so far there is still no method can adequately preserve important image contents and structure w... 详细信息
来源: 评论
Padding-Aware Learned Image Compression
Padding-Aware Learned Image Compression
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IEEE International Symposium on Circuits and systems (ISCAS)
作者: Haotian Zhang Junqi Liao Yiheng Jiang Li Li Dong Liu CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei China
For current learned image compression methods, padding input images is necessary to meet the resolution requirements of down-sampling layers. However, the impact of padding has not been studied thoroughly. Most previo...
来源: 评论