5 papers
Multi-Modal Hyper-Graph Fusion for Low-Light Crowd Counting
Hao-Yuan Ma, Li Zhang, Yushi Qiu +3
Crowd counting is a fundamental task in computer vision. However, crowd counting in low-light environments remains largely underexplored, despite its practical importance in the re…
MambaCount: Efficient Text-guided Open-vocabulary Object Counting with Spatial Sparse State Space Duality Block
Hao-Yuan Ma, Li Zhang, Minjie Qiang +1
Text-guided Open-vocabulary Object Counting (TOOC) aims to estimate the number of objects described by text prompts, which is particularly challenging in dense scenes with large sc…
Test-Time Training for Robust Text-Guided Open-Vocabulary Object Counting
Hao-Yuan Ma, Yuda Zou, Li Zhang +1
Text-guided Open-vocabulary Object Counting (TOOC) enables counting arbitrary object categories specified by text prompts, offering substantially greater flexibility than conventio…
RT-Counter: Real-Time Text-Guided Open-Vocabulary Object Counting
Hao-Yuan Ma, Li Zhang, Zhiwei Zhu +1
Text-guided open-vocabulary object counting (TOOC) aims to count objects belonging to the categories specified by natural language descriptions. Although vision-language pre-traine…
VMambaCC: A Visual State Space Model for Crowd Counting
Hao-Yuan Ma, Li Zhang, Shuai Shi
As a deep learning model, Visual Mamba (VMamba) has a low computational complexity and a global receptive field, which has been successful applied to image classification and detec…