7 citations · 12 across the 4 of their papers we have counts for
7 papers
DR.VIC: Decomposition and Reasoning for Video Individual Counting
Tao Han, Lei Bai, Junyu Gao +2
Pedestrian counting is a fundamental tool for understanding pedestrian patterns and crowd flow analysis. Existing works (e.g., image-level pedestrian counting, crossline crowd coun…
An Approach for Combining Multimodal Fusion and Neural Architecture Search Applied to Knowledge Tracing
Xinyi Ding, Tao Han, Yili Fang +1
Knowledge Tracing is the process of tracking mastery level of different skills of students for a given learning domain. It is one of the key components for building adaptive learni…
LDC-Net: A Unified Framework for Localization, Detection and Counting in Dense Crowds
Qi wang, Tao Han, Junyu Gao +2
The rapid development in visual crowd analysis shows a trend to count people by positioning or even detecting, rather than simply summing a density map. It also enlightens us back…
Unsupervised Semantic Aggregation and Deformable Template Matching for Semi-Supervised Learning
Tao Han, Junyu Gao, Yuan Yuan +1
Unlabeled data learning has attracted considerable attention recently. However, it is still elusive to extract the expected high-level semantic feature with mere unsupervised learn…
Neuron Linear Transformation: Modeling the Domain Shift for Crowd Counting
Qi Wang, Tao Han, Junyu Gao +1
Cross-domain crowd counting (CDCC) is a hot topic due to its importance in public safety. The purpose of CDCC is to alleviate the domain shift between the source and target domain.…
Focus on Semantic Consistency for Cross-domain Crowd Understanding
Tao Han, Junyu Gao, Yuan Yuan +1
For pixel-level crowd understanding, it is time-consuming and laborious in data collection and annotation. Some domain adaptation algorithms try to liberate it by training models w…