Additionally, the feature fusion module maximizes the utilization of reference view cues to enhance the human pose estimation in the current view. Experiments conducted on the Human3.6m dataset demonstrate a reduction in the average MPJPE to 18.3mm using our model.Dandan Sun...
[ECCV 2020] This is the official implementation of 3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for 3D Object Detection - rasd3/3D-CVF
Notably, the proposed MCAB promotes feature fusion from two viewpoints by employing bidirectional cross-attention, as opposed to an unidirectional flow from left to right or vice versa. This approach results in an efficient cross-view interaction from both branches. By leveraging the advantages of ...
3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for 3D Object Detection In this paper, we propose a new deep architecture for fusing camera and LiDAR sensors for 3D object detection. Because the camera and LiDAR sensor signals ... JH Yoo,Y Kim,J ...
Human pose estimation based on cross-view feature fusion Dandan Sun,Siqi Wang,Hailun Xia,... - 《Visual Computer》 - 2024 - 被引量: 0 Noise-Robust 3D Pose Estimation Using Appearance Similarity Based on the Distributed Multiple Views Hwang, Taemin,Kim, Minjoon - Sensors (14248220) - 2024 ...
Adaptive partial graph learning and fusion for incomplete multi‐view clustering Most of existing multi‐view clustering methods assume that different feature views of data are fully observed. However, it is common that only portions of... X Zheng,X Liu,J Chen,... - 《International Journal of...
Diverse feature representations may combat this problem from different aspects; as visual data objects described by multiple features can be decomposed into multiple views, thus often provide complementary information. In this paper, we propose a cross-view fusion algorithm that leads to a similarity ...
Late fusion incomplete multi-view clustering. Parameter-free auto-weighted multiple graph learning: a framework for multi-view clustering and semi-supervised classification. Learning a joint affinity graph for multiview subspace clustering. Gmc: graph-based multi-view clustering. Graph learning for multi...
The second challenge is addressed by a multiview CNN fusion model through a combination layer connecting the representation layers of RGB view and depth view. Comprehensive experiments on four benchmark datasets demonstrate the significant and consistent improvements of the proposed approach over other ...
Spindle net: person re-identification with human body region guided feature decomposition and fusion. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, 2017. 1077--1085. Google Scholar [32] Barbosa I B, Cristani M, Bue A D, et al. Re...