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20212023
most citedSpatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction

61 citations · 79 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG202361 cited

Spatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction

Guangyin Jin, Lingbo Liu, Fuxian Li +1

Traffic congestion event prediction is an important yet challenging task in intelligent transportation systems. Many existing works about traffic prediction integrate various tempo…

cs.CV20232 cited

STEERER: Resolving Scale Variations for Counting and Localization via Selective Inheritance Learning

Tao Han, Lei Bai, Lingbo Liu +1

Scale variation is a deep-rooted problem in object counting, which has not been effectively addressed by existing scale-aware algorithms. An important factor is that they typically…

cs.LG20231 cited

Long-term Wind Power Forecasting with Hierarchical Spatial-Temporal Transformer

Yang Zhang, Lingbo Liu, Xinyu Xiong +3

Wind power is attracting increasing attention around the world due to its renewable, pollution-free, and other advantages. However, safely and stably integrating the high permeabil…

cs.CV20233 cited

Urban Regional Function Guided Traffic Flow Prediction

Kuo Wang, Lingbo Liu, Yang Liu +3

The prediction of traffic flow is a challenging yet crucial problem in spatial-temporal analysis, which has recently gained increasing interest. In addition to spatial-temporal cor…

cs.CV202212 cited

Prompt-Matched Semantic Segmentation

Lingbo Liu, Jianlong Chang, Bruce X. B. Yu +3

The objective of this work is to explore how to effectively and efficiently adapt pre-trained visual foundation models to various downstream tasks of semantic segmentation. Previou…

cs.CV2021

Unconstrained Face Sketch Synthesis via Perception-Adaptive Network and A New Benchmark

Lin Nie, Lingbo Liu, Zhengtao Wu +1

Face sketch generation has attracted much attention in the field of visual computing. However, existing methods either are limited to constrained conditions or heavily rely on vari…