Paper Summary27 Revisiting Skeleton-based Action Recognition, CVPR’22 논문 링크 : https://openaccess.thecvf.com/content/CVPR2022/papers/Duan_Revisiting_Skeleton-Based_Action_Recognition_CVPR_2022_paper.pdfAbstractGCN-based methods are subject to limitations in robustness, interoperability, and scalability. In this work, we propose PoseConv3D, a new approach to skeleton-based action recognition. PoseConv3D relies on a 3D heatmap volume instead of a graph sequence as th.. 2023. 7. 21. DG-STGCN: Dynamic Spatial-Temporal Modeling for Skeleton-based Action Recognition, ACM MM’22 논문 링크 : https://arxiv.org/pdf/2210.05895.pdf Abstract We note that existing GCN based approaches primarily rely on prescribed graphical structures (i.e., a manually defined topology of skeleton joints), which limits their flexibility to capture complicated correlations between joints. To move beyond this limitation, we propose a new framework for skeleton-based action recognition, namely Dynamic.. 2023. 7. 21. Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild, ECCV’20 논문 링크 : https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123570035.pdfAbstractWe present a method that infers spatial arrangements and shapes of humans and objects in a globally consistent 3D scene, all from a single image in-the-wild captured in an uncontrolled environment. Notably, our method runs on datasets without any scene- or object level 3D supervision. Our key insight is that co.. 2023. 7. 21. Learning Motion Priors for 4D Human Body Capture in 3D Scenes, ICCV’21 논문 링크 : https://openaccess.thecvf.com/content/ICCV2021/papers/Zhang_Learning_Motion_Priors_for_4D_Human_Body_Capture_in_3D_ICCV_2021_paper.pdfAbstractCapturing realistic human scene interactions, while dealing with occlusions and partial views, is challenging. We address this problem by proposing LEMO: LEarning human MOtion priors for 4D human body capture. By leveraging the large scale motion c.. 2023. 7. 21. 이전 1 2 3 4 5 ··· 7 다음