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20192022
most citedBilinear Representation for Language-based Image Editing Using Conditional Generative Adversarial Networks

26 citations · 75 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2022★ 12 cited

Synthesizing Coherent Story with Auto-Regressive Latent Diffusion Models

Xichen Pan, Pengda Qin, Yuhong Li +2

Conditioned diffusion models have demonstrated state-of-the-art text-to-image synthesis capacity. Recently, most works focus on synthesizing independent images; While for real-worl…

cs.CL2021

InfoBehavior: Self-supervised Representation Learning for Ultra-long Behavior Sequence via Hierarchical Grouping

Runshi Liu, Pengda Qin, Yuhong Li +4

E-commerce companies have to face abnormal sellers who sell potentially-risky products. Typically, the risk can be identified by jointly considering product content (e.g., title an…

cs.CL2021★ 1 cited

TVDIM: Enhancing Image Self-Supervised Pretraining via Noisy Text Data

Pengda Qin, Yuhong Li, Kefeng Deng +1

Among ubiquitous multimodal data in the real world, text is the modality generated by human, while image reflects the physical world honestly. In a visual understanding application…

cs.CV2020★ 7 cited

GAP++: Learning to generate target-conditioned adversarial examples

Xiaofeng Mao, Yuefeng Chen, Yuhong Li +2

Adversarial examples are perturbed inputs which can cause a serious threat for machine learning models. Finding these perturbations is such a hard task that we can only use the ite…

cs.CV2019

Learning To Characterize Adversarial Subspaces

Xiaofeng Mao, Yuefeng Chen, Yuhong Li +2

Deep Neural Networks (DNNs) are known to be vulnerable to the maliciously generated adversarial examples. To detect these adversarial examples, previous methods use artificially de…

cs.LG2019★ 3 cited

Self-supervised Adversarial Training

Kejiang Chen, Hang Zhou, Yuefeng Chen +6

Recent work has demonstrated that neural networks are vulnerable to adversarial examples. To escape from the predicament, many works try to harden the model in various ways, in whi…

cs.CV2019★ 26 cited

Self-Supervised Learning For Few-Shot Image Classification

Da Chen, Yuefeng Chen, Yuhong Li +3

Few-shot image classification aims to classify unseen classes with limited labelled samples. Recent works benefit from the meta-learning process with episodic tasks and can fast ad…

cs.CV2019★ 26 cited

Bilinear Representation for Language-based Image Editing Using Conditional Generative Adversarial Networks

Xiaofeng Mao, Yuefeng Chen, Yuhong Li +3

The task of Language-Based Image Editing (LBIE) aims at generating a target image by editing the source image based on the given language description. The main challenge of LBIE is…