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20182026
most citedSpatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction

61 citations · 93 across the 17 of their papers we have counts for

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17 papers · 1 filter

cs.CV2023★ 1 cited

SQLNet: Scale-Modulated Query and Localization Network for Few-Shot Class-Agnostic Counting

Hefeng Wu, Yandong Chen, Lingbo Liu +3

The class-agnostic counting (CAC) task has recently been proposed to solve the problem of counting all objects of an arbitrary class with several exemplars given in the input image…

cs.CV2023

DenseLight: Efficient Control for Large-scale Traffic Signals with Dense Feedback

Junfan Lin, Yuying Zhu, Lingbo Liu +3

Traffic Signal Control (TSC) aims to reduce the average travel time of vehicles in a road network, which in turn enhances fuel utilization efficiency, air quality, and road safety,…

cs.CV2023★ 3 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.CV2022

Being Comes from Not-being: Open-vocabulary Text-to-Motion Generation with Wordless Training

Junfan Lin, Jianlong Chang, Lingbo Liu +4

Text-to-motion generation is an emerging and challenging problem, which aims to synthesize motion with the same semantics as the input text. However, due to the lack of diverse lab…

cs.CV2022★ 12 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.CV2022★ 2 cited

Heterogeneous Semantic Transfer for Multi-label Recognition with Partial Labels

Tianshui Chen, Tao Pu, Lingbo Liu +3

Multi-label image recognition with partial labels (MLR-PL), in which some labels are known while others are unknown for each image, may greatly reduce the cost of annotation and th…