视觉与机器人

多模态信息融合

面向图像、视频、多传感器和跨模态感知的信息融合，包括 Image Fusion、红外可见光、遥感、医学影像、LiDAR/雷达/相机和音视频融合。

2025-12-04 至 2025-12-04 共收录 2 篇信号源：cs.CV, eess.IV, eess.SP, cs.RO, cs.MM

1. 遥感融合与全色锐化 1 篇

2503.23793 2025-12-04 cs.CV 79%

Pan-LUT: Efficient Pan-sharpening via Learnable Look-Up Tables

Pan-LUT：通过可学习的查找表实现高效的全景锐化

Zhongnan Cai, Yingying Wang, Hui Zheng, Panwang Pan, ZiXu Lin, Ge Meng, Chenxin Li, Chunming He, Jiaxin Xie, Yunlong Lin, Junbin Lu, Yue Huang, Xinghao Ding

机构 * Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University（教育部多媒体可信感知与高效计算重点实验室，厦门大学）； ByteDance（字节跳动）； The Chinese University of Hong Kong（香港中文大学）； Duke University（杜克大学）； University of Washington（华盛顿大学）

专题命中遥感融合与全色锐化：pan-sharpening(title,abstract)；分类 cs.CV

AI总结 Pan-LUT通过可学习的查找表实现高效全景锐化，适用于大遥感图像，兼具高性能与低计算开销。

2. 音视频/视觉语言融合 1 篇

2508.17282 2025-12-04 cs.AI cs.SD 50%

ERF-BA-TFD+: A Multimodal Model for Audio-Visual Deepfake Detection

ERF-BA-TFD+: 一种用于音频视觉深度伪造检测的多模态模型

Xin Zhang, Jiaming Chu, Jian Zhao, Yuchu Jiang, Xu Yang, Lei Jin, Chi Zhang, Xuelong Li

专题命中音视频/视觉语言融合：audio-visual fusion(abstract)

AI总结 ERF-BA-TFD+通过结合增强接收场和音频视觉融合，提出了一种多模态深度伪造检测模型，在DDL-AV数据集上实现了最先进的检测性能。

Comments The paper is withdrawn after discovering a flaw in the theoretical derivation presented in Section Method. The incorrect step leads to conclusions that are not supported by the corrected derivation. We plan to reconstruct the argument and will release an updated version once the issue is fully resolved