activity
20192022
most citedFast Batch Nuclear-norm Maximization and Minimization for Robust Domain Adaptation

18 citations · 63 across the 12 of their papers we have counts for

collaborators

17 papers

cs.CV20231 cited

R&B: Region and Boundary Aware Zero-shot Grounded Text-to-image Generation

Jiayu Xiao, Henglei Lv, Liang Li +2

Recent text-to-image (T2I) diffusion models have achieved remarkable progress in generating high-quality images given text-prompts as input. However, these models fail to convey ap…

cs.LG20221 cited

Automatic Relation-aware Graph Network Proliferation

Shaofei Cai, Liang Li, Xinzhe Han +3

Graph neural architecture search has sparked much attention as Graph Neural Networks (GNNs) have shown powerful reasoning capability in many relational tasks. However, the currentl…

cs.CV2022

Unsupervised Coherent Video Cartoonization with Perceptual Motion Consistency

Zhenhuan Liu, Liang Li, Huajie Jiang +4

In recent years, creative content generations like style transfer and neural photo editing have attracted more and more attention. Among these, cartoonization of real-world scenes…

cs.CV202217 cited

IR-GAN: Image Manipulation with Linguistic Instruction by Increment Reasoning

Zhenhuan Liu, Jincan Deng, Liang Li +4

Conditional image generation is an active research topic including text2image and image translation. Recently image manipulation with linguistic instruction brings new challenges o…

cs.CV20222 cited

Few Shot Generative Model Adaption via Relaxed Spatial Structural Alignment

Jiayu Xiao, Liang Li, Chaofei Wang +2

Training a generative adversarial network (GAN) with limited data has been a challenging task. A feasible solution is to start with a GAN well-trained on a large scale source domai…

cs.CL20211 cited

RNet:Relation-embedded Representation Reconstruction Network for Change Captioning

Yunbin Tu, Liang Li, Chenggang Yan +2

Change captioning is to use a natural language sentence to describe the fine-grained disagreement between two similar images. Viewpoint change is the most typical distractor in thi…