Zobrazeno 1 - 10
of 89
pro vyhledávání: '"Jia, Chuanmin"'
Autor:
Zhao, Yanchen, He, Wenxuan, Jia, Chuanmin, Wang, Qizhe, Li, Junru, Li, Yue, Lin, Chaoyi, Zhang, Kai, Zhang, Li, Ma, Siwei
In this paper, a hybrid video compression framework is proposed that serves as a demonstrative showcase of deep learning-based approaches extending beyond the confines of traditional coding methodologies. The proposed hybrid framework is founded upon
Externí odkaz:
http://arxiv.org/abs/2402.08397
Autor:
Jia, Chuanmin, Ye, Feng, Dong, Fanke, Lin, Kai, Chiariglione, Leonardo, Ma, Siwei, Sun, Huifang, Gao, Wen
The rapid advancement of artificial intelligence (AI) technology has led to the prioritization of standardizing the processing, coding, and transmission of video using neural networks. To address this priority area, the Moving Picture, Audio, and Dat
Externí odkaz:
http://arxiv.org/abs/2309.07589
Recently, the bio-inspired spike camera with continuous motion recording capability has attracted tremendous attention due to its ultra high temporal resolution imaging characteristic. Such imaging feature results in huge data storage and transmissio
Externí odkaz:
http://arxiv.org/abs/2306.14108
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology 2024
In this age of information, images are a critical medium for storing and transmitting information. With the rapid growth of image data amount, visual compression and visual data perception are two important research topics attracting a lot attention.
Externí odkaz:
http://arxiv.org/abs/2304.06896
During the past decade, the Unmanned-Aerial-Vehicles (UAVs) have attracted increasing attention due to their flexible, extensive, and dynamic space-sensing capabilities. The volume of video captured by UAVs is exponentially growing along with the inc
Externí odkaz:
http://arxiv.org/abs/2301.06115
Video Coding for Machines (VCM) aims to compress visual signals for machine analysis. However, existing methods only consider a few machines, neglecting the majority. Moreover, the machine's perceptual characteristics are not leveraged effectively, r
Externí odkaz:
http://arxiv.org/abs/2211.06797
Traditional image/video compression aims to reduce the transmission/storage cost with signal fidelity as high as possible. However, with the increasing demand for machine analysis and semantic monitoring in recent years, semantic fidelity rather than
Externí odkaz:
http://arxiv.org/abs/2209.02574
End-to-end optimized neural image compression (NIC) has obtained superior lossy compression performance recently. In this paper, we consider the problem of rate-distortion (R-D) characteristic analysis and modeling for NIC. We make efforts to formula
Externí odkaz:
http://arxiv.org/abs/2106.12954
Optimized for pixel fidelity metrics, images compressed by existing image codec are facing systematic challenges when used for visual analysis tasks, especially under low-bitrate coding. This paper proposes a visual analysis-motivated rate-distortion
Externí odkaz:
http://arxiv.org/abs/2104.10315
Conceptual coding has been an emerging research topic recently, which encodes natural images into disentangled conceptual representations for compression. However, the compression performance of the existing methods is still sub-optimal due to the la
Externí odkaz:
http://arxiv.org/abs/2103.07131