no code implementations • 18 Mar 2024 • Liang Xu, Yizhou Zhou, Yichao Yan, Xin Jin, Wenhan Zhu, Fengyun Rao, Xiaokang Yang, Wenjun Zeng
Humans constantly interact with their surrounding environments.
no code implementations • 26 Dec 2023 • Liang Xu, Xintao Lv, Yichao Yan, Xin Jin, Shuwen Wu, Congsheng Xu, Yifan Liu, Yizhou Zhou, Fengyun Rao, Xingdong Sheng, Yunhui Liu, Wenjun Zeng, Xiaokang Yang
We also equip Inter-X with versatile annotations of more than 34K fine-grained human part-level textual descriptions, semantic interaction categories, interaction order, and the relationship and personality of the subjects.
no code implementations • 29 May 2023 • Feipeng Ma, Yizhou Zhou, Fengyun Rao, Yueyi Zhang, Xiaoyan Sun
This potential can be harnessed to create synthetic image-text pairs for training captioning models.
no code implementations • CVPR 2022 • Junyi Pan, Chong Sun, Yizhou Zhou, Ying Zhang, Chen Li
We first theoretically investigate how the weight coupling problem affects the network searching performance from a parameter distribution perspective, and then propose a novel supernet training strategy with a Distribution Consistent Constraint that can provide a good measurement for the extent to which two architectures can share weights.
1 code implementation • CVPR 2021 • Guangting Wang, Yizhou Zhou, Chong Luo, Wenxuan Xie, Wenjun Zeng, Zhiwei Xiong
The proxy task is to estimate the position and size of the image patch in a sequence of video frames, given only the target bounding box in the first frame.
no code implementations • 28 Jan 2021 • Yizhou Zhou, Chong Luo, Xiaoyan Sun, Zheng-Jun Zha, Wenjun Zeng
We believe that VAE$^2$ is also applicable to other stochastic sequence prediction problems where training data are lack of stochasticity.
1 code implementation • 17 Jan 2021 • Juntao Huang, Yizhou Zhou, Wen-An Yong
First, we use a single matrix to represent the stoichiometric coefficients for both the reactants and products in a system without catalysis reactions.
no code implementations • 28 Sep 2020 • Juntao Huang, Zhiting Ma, Yizhou Zhou, Wen-An Yong
In this work, we develop a method for learning interpretable, thermodynamically stable and Galilean invariant partial differential equations (PDEs) based on the Conservation-dissipation Formalism of irreversible thermodynamics.
no code implementations • CVPR 2020 • Yizhou Zhou, Xiaoyan Sun, Chong Luo, Zheng-Jun Zha, Wen-Jun Zeng
Based on the probability space, we further generate new fusion strategies which achieve the state-of-the-art performance on four well-known action recognition datasets.
1 code implementation • 23 Jun 2019 • Yizhou Zhou, Xiaoyan Sun, Chong Luo, Zheng-Jun Zha, Wen-Jun Zeng
Accordingly, a hybrid network representation is presented which enables us to leverage the Variational Dropout so that the approximation of the posterior distribution becomes fully gradient-based and highly efficient.
no code implementations • CVPR 2019 • Yizhou Zhou, Xiaoyan Sun, Zheng-Jun Zha, Wenjun Zeng
Recent efforts have shown the importance of context on deep convolutional neural network based semantic segmentation.
no code implementations • CVPR 2018 • Yizhou Zhou, Xiaoyan Sun, Zheng-Jun Zha, Wen-Jun Zeng
Recent attempts use 3D convolutional neural networks (CNNs) to explore spatio-temporal information for human action recognition.