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pro vyhledávání: '"DING DanDan"'
The enhanced Deep Hierarchical Video Compression-DHVC 2.0-has been introduced. This single-model neural video codec operates across a broad range of bitrates, delivering not only superior compression performance to representative methods but also imp
Externí odkaz:
http://arxiv.org/abs/2410.02598
Publikováno v:
口腔疾病防治, Vol 29, Iss 6, Pp 383-387 (2021)
Objective To investigate the expression of brain expressed X-linked gene 1(Bex1) and nuclear factor-kBp65 (NF-kBp65) in tongue squamous cell carcinoma, and its significance. Methods Immunohistochemistry was used to detect the expression of Bex1 and N
Externí odkaz:
https://doaj.org/article/28b6cc1520d04961af9815a0234b6d09
Despite considerable progress being achieved in point cloud geometry compression, there still remains a challenge in effectively compressing large-scale scenes with sparse surfaces. Another key challenge lies in reducing decoding latency, a crucial r
Externí odkaz:
http://arxiv.org/abs/2404.13550
While convolution and self-attention are extensively used in learned image compression (LIC) for transform coding, this paper proposes an alternative called Contextual Clustering based LIC (CLIC) which primarily relies on clustering operations and lo
Externí odkaz:
http://arxiv.org/abs/2401.11615
Publikováno v:
Jixie qiangdu, Vol 38, Pp 1130-1134 (2016)
To establish a rigid modle and a rigid-flexible coupling model of the transmission system of a coal winning machine haulage part,based on the theory of non-linear contact theory and multi-body dynamic. Applying ANSYS software to the rigid gear of fle
Externí odkaz:
https://doaj.org/article/786d9c4ba3fb42c88fd61fc64ce731ab
This work extends the multiscale structure originally developed for point cloud geometry compression to point cloud attribute compression. To losslessly encode the attribute while maintaining a low bitrate, accurate probability prediction is critical
Externí odkaz:
http://arxiv.org/abs/2303.12917
This work extends the Multiscale Sparse Representation (MSR) framework developed for static Point Cloud Geometry Compression (PCGC) to support the dynamic PCGC through the use of multiscale inter conditional coding. To this end, the reconstruction of
Externí odkaz:
http://arxiv.org/abs/2301.12165
A learning-based adaptive loop filter is developed for the Geometry-based Point Cloud Compression (G-PCC) standard to reduce attribute compression artifacts. The proposed method first generates multiple Most-Probable Sample Offsets (MPSOs) as potenti
Externí odkaz:
http://arxiv.org/abs/2209.08276
Publikováno v:
In Journal of Visual Communication and Image Representation October 2024 104
This study develops a unified Point Cloud Geometry (PCG) compression method through the processing of multiscale sparse tensor-based voxelized PCG. We call this compression method SparsePCGC. The proposed SparsePCGC is a low complexity solution becau
Externí odkaz:
http://arxiv.org/abs/2111.10633