1 code implementation • 12 Sep 2022 • Shilv Cai, Zhijun Zhang, Liqun Chen, Luxin Yan, Sheng Zhong, Xu Zou
We implement the IAT in a mathematical invertible manner on a single rate Invertible Neural Network (INN) based model and the quality level (QLevel) would be fed into the IAT to generate scaling and bias tensors.
no code implementations • CVPR 2022 • Leizhen Dong, Zhimin Li, Kunlun Xu, Zhijun Zhang, Luxin Yan, Sheng Zhong, Xu Zou
Specifically, the Object Query would be initialized via category priors represented by an external object detection model to yield better performance.
no code implementations • 24 Feb 2022 • Kunlun Xu, Zhimin Li, Zhijun Zhang, Leizhen Dong, Wenhui Xu, Luxin Yan, Sheng Zhong, Xu Zou
Moreover, we also use an actor branch to get interaction prediction of the actor and propose a novel composition strategy based on center-point indexing to generate the final HOI prediction.
no code implementations • 1 Dec 2021 • Yanjie Wang, Xu Zou, Zhijun Zhang, Wenhui Xu, Liqun Chen, Sheng Zhong, Luxin Yan, Guodong Wang
Detecting oriented objects along with estimating their rotation information is one crucial step for analyzing remote sensing images.
1 code implementation • 8 Nov 2021 • Qinkai Zheng, Xu Zou, Yuxiao Dong, Yukuo Cen, Da Yin, Jiarong Xu, Yang Yang, Jie Tang
To bridge this gap, we present the Graph Robustness Benchmark (GRB) with the goal of providing a scalable, unified, modular, and reproducible evaluation for the adversarial robustness of GML models.
1 code implementation • ICCV 2021 • Xiangyun Zhao, Xu Zou, Ying Wu
Once an MD is learned, it is able to use a few samples of a novel class to directly compute its prototype to fulfill the online morphing process.
1 code implementation • 12 Jun 2021 • Xu Zou, Qinkai Zheng, Yuxiao Dong, Xinyu Guan, Evgeny Kharlamov, Jialiang Lu, Jie Tang
In the GIA scenario, the adversary is not able to modify the existing link structure and node attributes of the input graph, instead the attack is performed by injecting adversarial nodes into it.
3 code implementations • NeurIPS 2021 • Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, Jie Tang
Text-to-Image generation in the general domain has long been an open problem, which requires both a powerful generative model and cross-modal understanding.
Ranked #51 on Text-to-Image Generation on COCO (using extra training data)
1 code implementation • 19 Mar 2021 • Xu Zou, Da Yin, Qingyang Zhong, Ming Ding, Hongxia Yang, Zhilin Yang, Jie Tang
To tackle this challenge, we propose an innovative method, inverse prompting, to better control text generation.
no code implementations • 1 Mar 2021 • Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, Hongxia Yang
In this work, we construct the largest dataset for multimodal pretraining in Chinese, which consists of over 1. 9TB images and 292GB texts that cover a wide range of domains.
2 code implementations • 19 May 2020 • Yukuo Cen, Jianwei Zhang, Xu Zou, Chang Zhou, Hongxia Yang, Jie Tang
Recent works usually give an overall embedding from a user's behavior sequence.
no code implementations • ICCV 2019 • Xu Zou, Sheng Zhong, Luxin Yan, Xiangyun Zhao, Jiahuan Zhou, Ying Wu
In this paper, we propose a novel Hierarchical Structured Landmark Ensemble (HSLE) model for learning robust facial landmark detection, by using it as the structural constraints.
no code implementations • 25 Sep 2019 • Xu Zou, Qiuye Jia, Jianwei Zhang, Chang Zhou, Zijun Yao, Hongxia Yang, Jie Tang
In this paper, we propose a method named Dimensional reweighting Graph Convolutional Networks (DrGCNs), to tackle the problem of variance between dimensional information in the node representations of GCNs.
2 code implementations • 4 Jul 2019 • Xu Zou, Qiuye Jia, Jianwei Zhang, Chang Zhou, Hongxia Yang, Jie Tang
Graph Convolution Networks (GCNs) are becoming more and more popular for learning node representations on graphs.
4 code implementations • 5 May 2019 • Yukuo Cen, Xu Zou, Jianwei Zhang, Hongxia Yang, Jingren Zhou, Jie Tang
Network embedding (or graph embedding) has been widely used in many real-world applications.
Ranked #1 on Link Prediction on Amazon
1 code implementation • CVPR 2018 • Yan Wang, Lequn Wang, Yurong You, Xu Zou, Vincent Chen, Serena Li, Gao Huang, Bharath Hariharan, Kilian Q. Weinberger
Not all people are equally easy to identify: color statistics might be enough for some cases while others might require careful reasoning about high- and low-level details.
Ranked #12 on Person Re-Identification on CUHK03 detected