Zobrazeno 1 - 10
of 768
pro vyhledávání: '"Ma, Siwei"'
The Human Visual System (HVS), with its intricate sophistication, is capable of achieving ultra-compact information compression for visual signals. This remarkable ability is coupled with high generalization capability and energy efficiency. By contr
Externí odkaz:
http://arxiv.org/abs/2411.14135
For decades, the Bj{\o}ntegaard Delta (BD) has been the metric for evaluating codec Rate-Distortion (R-D) performance. Yet, in most studies, BD is determined using just 4-5 R-D data points, could this be sufficient? As codecs and quality metrics adva
Externí odkaz:
http://arxiv.org/abs/2410.12220
Multi-modality image fusion aims at fusing specific-modality and shared-modality information from two source images. To tackle the problem of insufficient feature extraction and lack of semantic awareness for complex scenes, this paper focuses on how
Externí odkaz:
http://arxiv.org/abs/2407.06159
Unsupervised domain adaptation (UDA) techniques are vital for semantic segmentation in geosciences, effectively utilizing remote sensing imagery across diverse domains. However, most existing UDA methods, which focus on domain alignment at the high-l
Externí odkaz:
http://arxiv.org/abs/2404.04531
3D Gaussian Splatting (3DGS) has marked a significant breakthrough in the realm of 3D scene reconstruction and novel view synthesis. However, 3DGS, much like its predecessor Neural Radiance Fields (NeRF), struggles to accurately model physical reflec
Externí odkaz:
http://arxiv.org/abs/2404.01168
Recent progress in generative compression technology has significantly improved the perceptual quality of compressed data. However, these advancements primarily focus on producing high-frequency details, often overlooking the ability of generative mo
Externí odkaz:
http://arxiv.org/abs/2403.03736
Representing the Neural Radiance Field (NeRF) with the explicit voxel grid (EVG) is a promising direction for improving NeRFs. However, the EVG representation is not efficient for storage and transmission because of the terrific memory cost. Current
Externí odkaz:
http://arxiv.org/abs/2402.16366
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
Vehicles are no longer isolated entities in traffic environments, thanks to the development of IoV powered by 5G networks and their evolution into 6G. However, it is not enough for vehicles in a highly dynamic and complex traffic environment to make
Externí odkaz:
http://arxiv.org/abs/2401.04916
The accelerated proliferation of visual content and the rapid development of machine vision technologies bring significant challenges in delivering visual data on a gigantic scale, which shall be effectively represented to satisfy both human and mach
Externí odkaz:
http://arxiv.org/abs/2312.15622