4 citations · 4 across the 4 of their papers we have counts for
4 papers
CrowdMLP: Weakly-Supervised Crowd Counting via Multi-Granularity MLP
Mingjie Wang, Jun Zhou, Hao Cai +1
Existing state-of-the-art crowd counting algorithms rely excessively on location-level annotations, which are burdensome to acquire. When only count-level (weak) supervisory signal…
STNet: Scale Tree Network with Multi-level Auxiliator for Crowd Counting
Mingjie Wang, Hao Cai, Xianfeng Han +2
Crowd counting remains a challenging task because the presence of drastic scale variation, density inconsistency, and complex background can seriously degrade the counting accuracy…
Interlayer and Intralayer Scale Aggregation for Scale-invariant Crowd Counting
Mingjie Wang, Hao Cai, Jun Zhou +1
Crowd counting is an important vision task, which faces challenges on continuous scale variation within a given scene and huge density shift both within and across images. These ch…
BSD-GAN: Branched Generative Adversarial Network for Scale-Disentangled Representation Learning and Image Synthesis
Zili Yi, Zhiqin Chen, Hao Cai +3
We introduce BSD-GAN, a novel multi-branch and scale-disentangled training method which enables unconditional Generative Adversarial Networks (GANs) to learn image representations…