no code implementations • 24 Nov 2021 • Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Xiangyang Ji, Antoni Chan, Rong Jin
The generalization result of using pre-training data shows that the excess risk bound on a target task can be improved when the appropriate pre-training data is included in fine-tuning.
no code implementations • NeurIPS 2020 • Jia Wan, Antoni Chan
The annotation noise in crowd counting is not modeled in traditional crowd counting algorithms based on crowd density maps.
no code implementations • 25 Sep 2019 • Yufei Cui, Wuguannan Yao, Qiao Li, Antoni Chan, Chun Jason Xue
In this work, assuming that the exact posterior or a decent approximation is obtained, we propose a generic framework to approximate the output probability distribution induced by model posterior with a parameterized model and in an amortized fashion.
no code implementations • 16 May 2018 • Di Kang, Antoni Chan
In this paper, in contrast to using filters of different sizes, we utilize an image pyramid to deal with scale variations.
no code implementations • NeurIPS 2017 • Di Kang, Debarun Dhar, Antoni Chan
For example, for crowd counting, the camera perspective (e. g., camera angle and height) gives a clue about the appearance and scale of people in the scene.
no code implementations • CVPR 2017 • Weihong Ren, Jiandong Tian, Zhi Han, Antoni Chan, Yandong Tang
The existing snow/rain removal methods often fail for heavy snow/rain and dynamic scene.