462 citations · 1.9k across the 105 of their papers we have counts for
7 papers · 2 filters
Predicting Satisfied User and Machine Ratio for Compressed Images: A Unified Approach
Qi Zhang, Shanshe Wang, Xinfeng Zhang +3
Nowadays, high-quality images are pursued by both humans for better viewing experience and by machines for more accurate visual analysis. However, images are usually compressed bef…
A Semantic-Aware and Multi-Guided Network for Infrared-Visible Image Fusion
Xiaoli Zhang, Liying Wang, Libo Zhao +2
Multi-modality image fusion aims at fusing modality-specific (complementarity) and modality-shared (correlation) information from multiple source images. To tackle the problem of t…
Decomposition-based Unsupervised Domain Adaptation for Remote Sensing Image Semantic Segmentation
Xianping Ma, Xiaokang Zhang, Xingchen Ding +2
Unsupervised domain adaptation (UDA) techniques are vital for semantic segmentation in geosciences, effectively utilizing remote sensing imagery across diverse domains. However, mo…
Mirror-3DGS: Incorporating Mirror Reflections into 3D Gaussian Splatting
Jiarui Meng, Haijie Li, Yanmin Wu +4
3D Gaussian Splatting (3DGS) has significantly advanced 3D scene reconstruction and novel view synthesis. However, like Neural Radiance Fields (NeRF), 3DGS struggles with accuratel…
Unifying Generation and Compression: Ultra-low bitrate Image Coding Via Multi-stage Transformer
Naifu Xue, Qi Mao, Zijian Wang +2
Recent progress in generative compression technology has significantly improved the perceptual quality of compressed data. However, these advancements primarily focus on producing…
SPC-NeRF: Spatial Predictive Compression for Voxel Based Radiance Field
Zetian Song, Wenhong Duan, Yuhuai Zhang +3
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…
A Neural-network Enhanced Video Coding Framework beyond ECM
Yanchen Zhao, Wenxuan He, Chuanmin Jia +7
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 tradition…