Search Results for author: Xu Zou

Found 16 papers, 10 papers with code

High-Fidelity Variable-Rate Image Compression via Invertible Activation Transformation

1 code implementation12 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.

Image Compression

Effective Actor-centric Human-object Interaction Detection

no code implementations24 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.

Human-Object Interaction Detection

Learning Oriented Remote Sensing Object Detection via Naive Geometric Computing

no code implementations1 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.

object-detection Object Detection +1

Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning

1 code implementation8 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.

Adversarial Robustness Benchmarking +1

Morphable Detector for Object Detection on Demand

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.

object-detection Object Detection

TDGIA:Effective Injection Attacks on Graph Neural Networks

1 code implementation12 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.

Adversarial Attack

CogView: Mastering Text-to-Image Generation via Transformers

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)

Super-Resolution Zero-Shot Text-to-Image Generation

M6: A Chinese Multimodal Pretrainer

no code implementations1 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.

Image Generation

Learning Robust Facial Landmark Detection via Hierarchical Structured Ensemble

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.

Facial Landmark Detection

Dimensional Reweighting Graph Convolution Networks

no code implementations25 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.

Node Classification

Dimensional Reweighting Graph Convolutional Networks

2 code implementations4 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.

Node Classification

Resource Aware Person Re-identification across Multiple Resolutions

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.

Person Re-Identification

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