Multi View
Multi-view analysis integrates data from multiple perspectives to improve accuracy and robustness in various applications, primarily aiming to overcome limitations of single-view approaches. Current research focuses on developing efficient algorithms and model architectures, such as transformers and graph neural networks, to handle high-dimensional data and address challenges like data incompleteness, view misalignment, and computational constraints. This field is significant for advancing computer vision, medical image analysis, robotics, and other domains by enabling more accurate and reliable inferences from complex, multi-faceted data.
399papers
Papers - Page 18
July 24, 2023
Spatiotemporal Modeling Encounters 3D Medical Image Analysis: Slice-Shift UNet with Multi-View Fusion
C. I. Ugwu, S. Casarin, O. LanzMulti-View Vertebra Localization and Identification from CT Images
Han Wu, Jiadong Zhang, Yu Fang, Zhentao Liu, Nizhuan Wang, Zhiming Cui, Dinggang ShenSwinMM: Masked Multi-view with Swin Transformers for 3D Medical Image Segmentation
Yiqing Wang, Zihan Li, Jieru Mei, Zihao Wei, Li Liu, Chen Wang, Shengtian Sang, Alan Yuille, Cihang Xie, Yuyin Zhou
July 21, 2023
July 17, 2023
June 27, 2023
Multi-perspective Information Fusion Res2Net with RandomSpecmix for Fake Speech Detection
Shunbo Dong, Jun Xue, Cunhang Fan, Kang Zhu, Yujie Chen, Zhao LvMIMIC: Masked Image Modeling with Image Correspondences
Kalyani Marathe, Mahtab Bigverdi, Nishat Khan, Tuhin Kundu, Patrick Howe, Sharan Ranjit S, Anand Bhattad, Aniruddha Kembhavi, Linda G. Shapiro+1
June 26, 2023
June 16, 2023