Search Results for author: Wentao Wang

Found 13 papers, 8 papers with code

The KFIoU Loss for Rotated Object Detection

2 code implementations29 Jan 2022 Xue Yang, Yue Zhou, Gefan Zhang, Jirui Yang, Wentao Wang, Junchi Yan, Xiaopeng Zhang, Qi Tian

Differing from the well-developed horizontal object detection area whereby the computing-friendly IoU based loss is readily adopted and well fits with the detection metrics.

Object Detection In Aerial Images

Imbalanced Adversarial Training with Reweighting

no code implementations28 Jul 2021 Wentao Wang, Han Xu, Xiaorui Liu, Yaxin Li, Bhavani Thuraisingham, Jiliang Tang

Adversarial training has been empirically proven to be one of the most effective and reliable defense methods against adversarial attacks.

Towards the Memorization Effect of Neural Networks in Adversarial Training

no code implementations9 Jun 2021 Han Xu, Xiaorui Liu, Wentao Wang, Wenbiao Ding, Zhongqin Wu, Zitao Liu, Anil Jain, Jiliang Tang

In this work, we study the effect of memorization in adversarial trained DNNs and disclose two important findings: (a) Memorizing atypical samples is only effective to improve DNN's accuracy on clean atypical samples, but hardly improve their adversarial robustness and (b) Memorizing certain atypical samples will even hurt the DNN's performance on typical samples.

Adversarial Robustness

Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence

2 code implementations NeurIPS 2021 Xue Yang, Xiaojiang Yang, Jirui Yang, Qi Ming, Wentao Wang, Qi Tian, Junchi Yan

Taking the perspective that horizontal detection is a special case for rotated object detection, in this paper, we are motivated to change the design of rotation regression loss from induction paradigm to deduction methodology, in terms of the relation between rotation and horizontal detection.

Object Detection In Aerial Images

Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss

2 code implementations28 Jan 2021 Xue Yang, Junchi Yan, Qi Ming, Wentao Wang, Xiaopeng Zhang, Qi Tian

Boundary discontinuity and its inconsistency to the final detection metric have been the bottleneck for rotating detection regression loss design.

Object Detection In Aerial Images Small Object Detection

Parallel Multi-Resolution Fusion Network for Image Inpainting

no code implementations ICCV 2021 Wentao Wang, Jianfu Zhang, Li Niu, Haoyu Ling, Xue Yang, Liqing Zhang

Conventional deep image inpainting methods are based on auto-encoder architecture, in which the spatial details of images will be lost in the down-sampling process, leading to the degradation of generated results.

Image Inpainting

Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning

1 code implementation EMNLP 2020 Haochen Liu, Wentao Wang, Yiqi Wang, Hui Liu, Zitao Liu, Jiliang Tang

Extensive experiments on two real-world conversation datasets show that our framework significantly reduces gender bias in dialogue models while maintaining the response quality.

Dialogue Generation

Representation Learning from Limited Educational Data with Crowdsourced Labels

1 code implementation23 Sep 2020 Wentao Wang, Guowei Xu, Wenbiao Ding, Gale Yan Huang, Guoliang Li, Jiliang Tang, Zitao Liu

Extensive experiments conducted on three real-world data sets demonstrate the superiority of our framework on learning representations from limited data with crowdsourced labels, comparing with various state-of-the-art baselines.

Face Recognition Machine Translation +1

Data-to-Text Generation with Style Imitation

1 code implementation Findings of the Association for Computational Linguistics 2020 Shuai Lin, Wentao Wang, Zichao Yang, Xiaodan Liang, Frank F. Xu, Eric Xing, Zhiting Hu

That is, the model learns to imitate the writing style of any given exemplar sentence, with automatic adaptions to faithfully describe the content record.

Data-to-Text Generation Style Transfer

Differentiable Expected BLEU for Text Generation

no code implementations27 Sep 2018 Wentao Wang, Zhiting Hu, Zichao Yang, Haoran Shi, Eric P. Xing

Neural text generation models such as recurrent networks are typically trained by maximizing data log-likelihood based on cross entropy.

Image Captioning Machine Translation +2

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