1 code implementation • 20 Dec 2023 • Shiu-hong Kao, Jierun Chen, S. H. Gary Chan
Knowledge distillation (KD) has been recognized as an effective tool to compress and accelerate models.
no code implementations • 1 Dec 2023 • Tianlang He, Zhiqiu Xia, Jierun Chen, Haoliang Li, S. -H. Gary Chan
Unsupervised domain adaptation (UDA) seeks to bridge the domain gap between the target and source using unlabeled target data.
1 code implementation • 12 Jul 2023 • Weipeng Zhuo, Ka Ho Chiu, Jierun Chen, Ziqi Zhao, S. -H. Gary Chan, Sangtae Ha, Chul-Ho Lee
To build a prediction model to identify the floor number of a new RF signal upon its measurement, conventional approaches using the crowdsourced RF signals assume that at least few labeled signal samples are available on each floor.
2 code implementations • CVPR 2023 • Jierun Chen, Shiu-hong Kao, Hao He, Weipeng Zhuo, Song Wen, Chul-Ho Lee, S. -H. Gary Chan
To achieve faster networks, we revisit popular operators and demonstrate that such low FLOPS is mainly due to frequent memory access of the operators, especially the depthwise convolution.
1 code implementation • CVPR 2022 • Jierun Chen, Tianlang He, Weipeng Zhuo, Li Ma, Sangtae Ha, S. -H. Gary Chan
Extensive experiments on face recognition show that TVConv reduces the computational cost by up to 3. 1x and improves the corresponding throughput by 2. 3x while maintaining a high accuracy compared to the depthwise convolution.
no code implementations • 12 Jan 2021 • Jierun Chen, Song Wen, S. -H. Gary Chan
In this paper, we propose and study Wild-JDD, a novel learning framework for joint demosaicking and denoising in the wild.