31 citations · 58 across the 7 of their papers we have counts for
7 papers
Semi-supervised Counting via Pixel-by-pixel Density Distribution Modelling
Hui Lin, Zhiheng Ma, Rongrong Ji +4
This paper focuses on semi-supervised crowd counting, where only a small portion of the training data are labeled. We formulate the pixel-wise density value to regress as a probabi…
Gramformer: Learning Crowd Counting via Graph-Modulated Transformer
Hui Lin, Zhiheng Ma, Xiaopeng Hong +2
Transformer has been popular in recent crowd counting work since it breaks the limited receptive field of traditional CNNs. However, since crowd images always contain a large numbe…
LGViT: Dynamic Early Exiting for Accelerating Vision Transformer
Guanyu Xu, Jiawei Hao, Li Shen +4
Recently, the efficient deployment and acceleration of powerful vision transformers (ViTs) on resource-limited edge devices for providing multimedia services have become attractive…
Semi-supervised Crowd Counting via Density Agency
Hui Lin, Zhiheng Ma, Xiaopeng Hong +2
In this paper, we propose a new agency-guided semi-supervised counting approach. First, we build a learnable auxiliary structure, namely the density agency to bring the recognized…
Boosting Crowd Counting via Multifaceted Attention
Hui Lin, Zhiheng Ma, Rongrong Ji +2
This paper focuses on the challenging crowd counting task. As large-scale variations often exist within crowd images, neither fixed-size convolution kernel of CNN nor fixed-size at…
Object Counting: You Only Need to Look at One
Hui Lin, Xiaopeng Hong, Yabin Wang
This paper aims to tackle the challenging task of one-shot object counting. Given an image containing novel, previously unseen category objects, the goal of the task is to count al…
Direct Measure Matching for Crowd Counting
Hui Lin, Xiaopeng Hong, Zhiheng Ma +4
Traditional crowd counting approaches usually use Gaussian assumption to generate pseudo density ground truth, which suffers from problems like inaccurate estimation of the Gaussia…