25 citations · 34 across the 7 of their papers we have counts for
5 papers · 1 filter
Dynamic Spatial-temporal Hypergraph Convolutional Network for Skeleton-based Action Recognition
Shengqin Wang, Yongji Zhang, Hong Qi +2
Skeleton-based action recognition relies on the extraction of spatial-temporal topological information. Hypergraphs can establish prior unnatural dependencies for the skeleton. How…
Skeleton-based Action Recognition via Temporal-Channel Aggregation
Shengqin Wang, Yongji Zhang, Minghao Zhao +4
Skeleton-based action recognition methods are limited by the semantic extraction of spatio-temporal skeletal maps. However, current methods have difficulty in effectively combining…
Spirit Distillation: A Model Compression Method with Multi-domain Knowledge Transfer
Zhiyuan Wu, Yu Jiang, Minghao Zhao +4
Recent applications pose requirements of both cross-domain knowledge transfer and model compression to machine learning models due to insufficient training data and limited computa…
Spirit Distillation: Precise Real-time Semantic Segmentation of Road Scenes with Insufficient Data
Zhiyuan Wu, Yu Jiang, Chupeng Cui +3
Semantic segmentation of road scenes is one of the key technologies for realizing autonomous driving scene perception, and the effectiveness of deep Convolutional Neural Networks(C…
Activation Map Adaptation for Effective Knowledge Distillation
Zhiyuan Wu, Hong Qi, Yu Jiang +4
Model compression becomes a recent trend due to the requirement of deploying neural networks on embedded and mobile devices. Hence, both accuracy and efficiency are of critical imp…