no code implementations • 7 Apr 2024 • Peng Tu, Xun Zhou, Mingming Wang, Xiaojun Yang, Bo Peng, Ping Chen, Xiu Su, Yawen Huang, Yefeng Zheng, Chang Xu
Neural Radiance Fields (NeRF) have emerged as a paradigm-shifting methodology for the photorealistic rendering of objects and environments, enabling the synthesis of novel viewpoints with remarkable fidelity.
1 code implementation • NeurIPS 2023 • Yichao Cao, Qingfei Tang, Xiu Su, Chen Song, Shan You, Xiaobo Lu, Chang Xu
We conduct a deep analysis of the three hierarchical features inherent in visual HOI detectors and propose a method for high-level relation extraction aimed at VL foundation models, which we call HO prompt-based learning.
1 code implementation • 21 Aug 2023 • Mingkai Zheng, Shan You, Lang Huang, Xiu Su, Fei Wang, Chen Qian, Xiaogang Wang, Chang Xu
Moreover, to further boost the performance, we propose ``distributional consistency" as a more informative regularization to enable similar instances to have a similar probability distribution.
no code implementations • ICCV 2023 • Yichao Cao, Qingfei Tang, Feng Yang, Xiu Su, Shan You, Xiaobo Lu, Chang Xu
Human-Object Interaction (HOI) detection is a challenging computer vision task that requires visual models to address the complex interactive relationship between humans and objects and predict HOI triplets.
1 code implementation • 21 Apr 2023 • Mingkai Zheng, Xiu Su, Shan You, Fei Wang, Chen Qian, Chang Xu, Samuel Albanie
We investigate the potential of GPT-4~\cite{gpt4} to perform Neural Architecture Search (NAS) -- the task of designing effective neural architectures.
1 code implementation • 15 Jul 2022 • Jiyang Xie, Xiu Su, Shan You, Zhanyu Ma, Fei Wang, Chen Qian
Recently, community has paid increasing attention on model scaling and contributed to developing a model family with a wide spectrum of scales.
no code implementations • 5 Jul 2022 • Hongyan Xu, Xiu Su, Dadong Wang
Deep learning technology can be used as an assistive technology to help doctors quickly and accurately identify COVID-19 infections.
1 code implementation • 25 Mar 2022 • Xiu Su, Shan You, Jiyang Xie, Fei Wang, Chen Qian, ChangShui Zhang, Chang Xu
In BCNet, each channel is fairly trained and responsible for the same amount of network widths, thus each network width can be evaluated more accurately.
1 code implementation • 25 Jun 2021 • Xiu Su, Shan You, Jiyang Xie, Mingkai Zheng, Fei Wang, Chen Qian, ChangShui Zhang, Xiaogang Wang, Chang Xu
Vision transformers (ViTs) inherited the success of NLP but their structures have not been sufficiently investigated and optimized for visual tasks.
no code implementations • 11 Jun 2021 • Xiu Su, Shan You, Mingkai Zheng, Fei Wang, Chen Qian, ChangShui Zhang, Chang Xu
The operation weight for each path is represented as a convex combination of items in a dictionary with a simplex code.
no code implementations • CVPR 2021 • Xiu Su, Shan You, Fei Wang, Chen Qian, ChangShui Zhang, Chang Xu
In BCNet, each channel is fairly trained and responsible for the same amount of network widths, thus each network width can be evaluated more accurately.
1 code implementation • CVPR 2021 • Xiu Su, Tao Huang, Yanxi Li, Shan You, Fei Wang, Chen Qian, ChangShui Zhang, Chang Xu
One-shot neural architecture search (NAS) methods significantly reduce the search cost by considering the whole search space as one network, which only needs to be trained once.
no code implementations • ICLR 2021 • Xiu Su, Shan You, Tao Huang, Fei Wang, Chen Qian, ChangShui Zhang, Chang Xu
In this paper, to better evaluate each width, we propose a locally free weight sharing strategy (CafeNet) accordingly.
no code implementations • 28 Oct 2020 • Xiu Su, Shan You, Tao Huang, Hongyan Xu, Fei Wang, Chen Qian, ChangShui Zhang, Chang Xu
To deploy a well-trained CNN model on low-end computation edge devices, it is usually supposed to compress or prune the model under certain computation budget (e. g., FLOPs).