HumanAI18 ContactOpt: Optimizing Contact to Improve Grasps, CVPR’21 논문 링크 : https://openaccess.thecvf.com/content/CVPR2021/papers/Grady_ContactOpt_Optimizing_Contact_To_Improve_Grasps_CVPR_2021_paper.pdfAbstractGiven a hand mesh and an object mesh, a deep model trained on ground truth contact data infers desirable contact across the surfaces of the meshes. Then, ContactOpt efficiently optimizes the pose of the hand to achieve desirable contact using a differenti.. 2023. 7. 21. Leveraging Photometric Consistency over Time for Sparsely Supervised Hand-Object Reconstruction, CVPR’20 논문 링크 : https://openaccess.thecvf.com/content_CVPR_2020/papers/Hasson_Leveraging_Photometric_Consistency_Over_Time_for_Sparsely_Supervised_Hand-Object_Reconstruction_CVPR_2020_paper.pdfAbstractCollecting 3D ground-truth data for hand-object interactions is costly, tedious, and error-prone. To overcome this challenge we present a method to leverage photometric consistency across time when annotat.. 2023. 7. 21. 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. 이전 1 2 3 4 5 다음