92 citations · 326 across the 9 of their papers we have counts for
9 papers
T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation
Lijun Li, Zhelun Shi, Xuhao Hu +5
Text-to-image (T2I) models have rapidly advanced, enabling the generation of high-quality images from text prompts across various domains. However, these models present notable saf…
Open-Edit: Open-Domain Image Manipulation with Open-Vocabulary Instructions
Xihui Liu, Zhe Lin, Jianming Zhang +4
We propose a novel algorithm, named Open-Edit, which is the first attempt on open-domain image manipulation with open-vocabulary instructions. It is a challenging task considering…
Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis
Xihui Liu, Guojun Yin, Jing Shao +2
Semantic image synthesis aims at generating photorealistic images from semantic layouts. Previous approaches with conditional generative adversarial networks (GAN) show state-of-th…
CAMP: Cross-Modal Adaptive Message Passing for Text-Image Retrieval
Zihao Wang, Xihui Liu, Hongsheng Li +4
Text-image cross-modal retrieval is a challenging task in the field of language and vision. Most previous approaches independently embed images and sentences into a joint embedding…
Improving Referring Expression Grounding with Cross-modal Attention-guided Erasing
Xihui Liu, Zihao Wang, Jing Shao +2
Referring expression grounding aims at locating certain objects or persons in an image with a referring expression, where the key challenge is to comprehend and align various types…
Localization Guided Learning for Pedestrian Attribute Recognition
Pengze Liu, Xihui Liu, Junjie Yan +1
Pedestrian attribute recognition has attracted many attentions due to its wide applications in scene understanding and person analysis from surveillance videos. Existing methods tr…
Improving Deep Visual Representation for Person Re-identification by Global and Local Image-language Association
Dapeng Chen, Hongsheng Li, Xihui Liu +3
Person re-identification is an important task that requires learning discriminative visual features for distinguishing different person identities. Diverse auxiliary information ha…
Show, Tell and Discriminate: Image Captioning by Self-retrieval with Partially Labeled Data
Xihui Liu, Hongsheng Li, Jing Shao +2
The aim of image captioning is to generate captions by machine to describe image contents. Despite many efforts, generating discriminative captions for images remains non-trivial.…
HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis
Xihui Liu, Haiyu Zhao, Maoqing Tian +5
Pedestrian analysis plays a vital role in intelligent video surveillance and is a key component for security-centric computer vision systems. Despite that the convolutional neural…