实验分析 论文在两个大规模数据集(NTU-RGBD和Kinetics-Skeleton)上进行了评估。实验结果表明,MS-AAGCN在两个数据集上都达到了最新的最优性能,在 NTU-RGBD 数据集上分别提高了 +7.9%(交叉主体)和 +8.5%(交叉视角)。通过消融实验,验证了自适应图学习和 STC 注意力模块等组件对整体精度的贡献。模型还通过可视化注...
论文题目:Skeleton-based action recognition based on multidimensional adaptive dynamic temporal graph convolutional network 作者&团队:Xia Y, Gao Q, Wu W, et al. 1.江南大学机械工程学院 2.江苏省先进食品制造装备与技术重点实验室 发表期刊/会议:Engineering Applications of Artificial Intelligence 中科院分区:S...
To study skeleton-action recognition in the wild, we introduce Skeletics-152, a curated and 3-D pose-annotated subset of RGB videos sourced from Kinetics-700, a large-scale action dataset. We extend our study to include out-of-context actions by introducing Skeleton-Mimetics, a dataset ...
浅谈对Two-Stream 3D Convolutional Neural Network for Human Skeleton-Based Action Recognition,基于人体骨架的动作识 这一篇就是讲3DCNN的,作者提出3DCNN是一种从空间和时间维度学习特征的强大工具,但是在基于骨架的动作识别中的应用还是第一次,所以作者提出3DCNN在双流基于骨骼的动作识别方向上的应用。作者通过将骨骼...
Considering the problem that skeleton action recognition can not fully exploit spatio-temporal features, a skeleton action recognition model based on Spatio-Temporal Feature Enhanced Graph Convolutional Network (STFE-GCN) is proposed in this paper. First
Ref: OpenMMTalk #1| Skeleton based action recognition _PoseC3D Ref: 行为识别(action recognition)目前的难点在哪? 行为识别综述 Ref: https://zhuanlan.zhihu.com/p/88945361 2. 行为识别方法 2.1 时空关键点(space-time interest points) 2.2 密集轨迹(dense-trajectories) 2.3 表观和光流并举(two-stream...
Skeleton-Based Action Recognition with Directed Graph Neural Network回到顶部 摘要因为骨架信息可以鲁棒地适应动态环境和复杂的背景,所以经常被广泛应用在动作识别任务上,现有的方法已经证实骨架中的关键点和骨头信息对动作识别任务非常有用。然而如何将两种类型的数据最大化地利用还没有被很好地解决。作者...
A OpenMMLAB toolbox for human pose estimation, skeleton-based action recognition, and action synthesis. deep-learningpytorchaction-recognitiongraph-convolutional-networkskeleton-based-action-recognition UpdatedNov 25, 2022 Python Walter0807/MotionBERT ...
论文翻译:Skeleton Based Human Action Recognition with Global Context-Aware Attention LSTM Networks,程序员大本营,技术文章内容聚合第一站。
(1) A novel 2D human skeleton action recognition model with spatial constraints, named 2D-SCHAR, is introduced to address the ambiguity and uncertainty associated with human action recognition in 2D ...