no code implementations • 18 Jul 2023 • Zhen Qin, Weixuan Sun, Kaiyue Lu, Hui Deng, Dongxu Li, Xiaodong Han, Yuchao Dai, Lingpeng Kong, Yiran Zhong
Meanwhile, it emphasizes a general paradigm for designing broadly more relative positional encoding methods that are applicable to linear transformers.
no code implementations • 15 Oct 2022 • Kaiyue Lu, Zexiang Liu, Jianyuan Wang, Weixuan Sun, Zhen Qin, Dong Li, Xuyang Shen, Hui Deng, Xiaodong Han, Yuchao Dai, Yiran Zhong
Therefore, we propose a feature fixation module to reweight the feature importance of the query and key before computing linear attention.
no code implementations • 28 Jul 2022 • Zexiang Liu, Dong Li, Kaiyue Lu, Zhen Qin, Weixuan Sun, Jiacheng Xu, Yiran Zhong
To address this issue, we propose a new framework to find optimal architectures for efficient Transformers with the neural architecture search (NAS) technique.
no code implementations • CVPR 2020 • Kaiyue Lu, Nick Barnes, Saeed Anwar, Liang Zheng
Specifically, we formulate image reconstruction from sparse depth as an auxiliary task during training that is supervised by the unlabelled gray-scale images.
no code implementations • ECCV 2018 • Kaiyue Lu, ShaoDi You, Nick Barnes
Image smoothing is a fundamental task in computer vision, that aims to retain salient structures and remove insignificant textures.