Chunfang Yang
Biographic Data
| ID | 7303626 |
|---|---|
| NAME | Chunfang Yang |
| GIVEN NAMES | Chunfang |
| FAMILY NAME | Yang |
| SIGNATURE | YANG C |
| AFFILIATIONS | Henan Key Laboratory of Cyberspace Situation Awareness, Zhengzhou, China |
| ORCID | 0000-0002-8599-2664 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Where to Go: A Spatial Social Force Graph Neural Network for Predicting Pedestrian Trajectories From Videos With Complex Motion Scenarios
Traditional pedestrian trajectory prediction models focus on spatio–temporal data without proper consideration of individual interactions with the environment, mutual interactions, and contextual information, resulting in low prediction performance in real applications. In this article, we propose a new pedestrian trajectory prediction model called spatial social force graph neural network (SSF-GNN). First, SSF-GNN adopts a gate recurrent unit (G…
Cig2s: A Cross-View Image Geo-Localization Model Based on G2S Transform Suitable for Center-Misaligned Scenarios
In multimedia social networks, the user's geo-location can be inferred by matching his shared images with the referenced satellite images, viz. cross-view image geo-localization. Although the existing most cross-view image geo-localization methods perform well in the center-misaligned scenario, in practical application, the shooting location of the query ground image is most likely not aligned with the center point of satellite images. Then, thei…
Centipeda minima: An update on its phytochemistry, pharmacology and safety
No prominent works on this page.
Centipeda minima: An update on its phytochemistry, pharmacology and safety
Cig2s: A Cross-View Image Geo-Localization Model Based on G2S Transform Suitable for Center-Misaligned Scenarios
In multimedia social networks, the user's geo-location can be inferred by matching his shared images with the referenced satellite images, viz. cross-view image geo-localization. Although the existing most cross-view image geo-localization methods perform well in the center-misaligned scenario, in practical application, the shooting location of the query ground image is most likely not aligned with the center point of satellite images. Then, thei…
Where to Go: A Spatial Social Force Graph Neural Network for Predicting Pedestrian Trajectories From Videos With Complex Motion Scenarios
Traditional pedestrian trajectory prediction models focus on spatio–temporal data without proper consideration of individual interactions with the environment, mutual interactions, and contextual information, resulting in low prediction performance in real applications. In this article, we propose a new pedestrian trajectory prediction model called spatial social force graph neural network (SSF-GNN). First, SSF-GNN adopts a gate recurrent unit (G…
Algorithm (1 works) · Allergic Rhinitis and Sensitization (1 works) · Anomaly Detection Techniques and Applications (1 works) · Artificial Intelligence (1 works) · Artificial neural network (1 works) · Autonomous Vehicle Technology and Safety (1 works) · Computer Science (1 works) · Computer vision (1 works) · Essential Oils and Antimicrobial Activity (1 works) · Evacuation and Crowd Dynamics (1 works)