30 citations · 54 across the 8 of their papers we have counts for
8 papers
CAKE: A Scalable Commonsense-Aware Framework For Multi-View Knowledge Graph Completion
Guanglin Niu, Bo Li, Yongfei Zhang +1
Knowledge graphs store a large number of factual triples while they are still incomplete, inevitably. The previous knowledge graph completion (KGC) models predict missing links bet…
Perform Like an Engine: A Closed-Loop Neural-Symbolic Learning Framework for Knowledge Graph Inference
Guanglin Niu, Bo Li, Yongfei Zhang +1
Knowledge graph (KG) inference aims to address the natural incompleteness of KGs, including rule learning-based and KG embedding (KGE) models. However, the rule learning-based mode…
Spatiotemporal Transformer for Video-based Person Re-identification
Tianyu Zhang, Longhui Wei, Lingxi Xie +4
Recently, the Transformer module has been transplanted from natural language processing to computer vision. This paper applies the Transformer to video-based person re-identificati…
UnrealPerson: An Adaptive Pipeline towards Costless Person Re-identification
Tianyu Zhang, Lingxi Xie, Longhui Wei +4
The main difficulty of person re-identification (ReID) lies in collecting annotated data and transferring the model across different domains. This paper presents UnrealPerson, a no…
Joint Semantics and Data-Driven Path Representation for Knowledge Graph Inference
Guanglin Niu, Bo Li, Yongfei Zhang +4
Inference on a large-scale knowledge graph (KG) is of great importance for KG applications like question answering. The path-based reasoning models can leverage much information ov…
AutoETER: Automated Entity Type Representation for Knowledge Graph Embedding
Guanglin Niu, Bo Li, Yongfei Zhang +2
Recent advances in Knowledge Graph Embedding (KGE) allow for representing entities and relations in continuous vector spaces. Some traditional KGE models leveraging additional type…