no code implementations • ECCV 2020 • Xin Xiong, Haipeng Xiong, Ke Xian, Chen Zhao, Zhiguo Cao, Xin Li
Depth completion is a widely studied problem of predicting a dense depth map from a sparse set of measurements and a single RGB image.
no code implementations • 26 Oct 2023 • Haipeng Xiong, Angela Yao
To improve regression performance over the entire range of data, we propose to construct hierarchical classifiers for solving imbalanced regression tasks.
1 code implementation • 20 Jul 2022 • Haipeng Xiong, Angela Yao
Through a series of experiments on carefully controlled synthetic data, we show that this counter-intuitive result is caused by imprecise ground truth local counts.
1 code implementation • ECCV 2020 • Liang Liu, Hao Lu, Hongwei Zou, Haipeng Xiong, Zhiguo Cao, Chunhua Shen
Inspired by scale weighing, we propose a novel 'counting scale' termed LibraNet where the count value is analogized by weight.
3 code implementations • 7 Jan 2020 • Haipeng Xiong, Hao Lu, Chengxin Liu, Liang Liu, Chunhua Shen, Zhiguo Cao
Visual counting, a task that aims to estimate the number of objects from an image/video, is an open-set problem by nature, i. e., the number of population can vary in [0, inf) in theory.
5 code implementations • ICCV 2019 • Haipeng Xiong, Hao Lu, Chengxin Liu, Liang Liu, Zhiguo Cao, Chunhua Shen
A dense region can always be divided until sub-region counts are within the previously observed closed set.
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