activity
20192024
most citedTowards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations

25 citations · 108 across the 23 of their papers we have counts for

collaborators
Showing 2022Show all

6 papers · 1 filter

cs.CL2022

Learning to Dub Movies via Hierarchical Prosody Models

Gaoxiang Cong, Liang Li, Yuankai Qi +6

Given a piece of text, a video clip and a reference audio, the movie dubbing (also known as visual voice clone V2C) task aims to generate speeches that match the speaker's emotion…

cs.CV2022

Entity-enhanced Adaptive Reconstruction Network for Weakly Supervised Referring Expression Grounding

Xuejing Liu, Liang Li, Shuhui Wang +4

Weakly supervised Referring Expression Grounding (REG) aims to ground a particular target in an image described by a language expression while lacking the correspondence between ta…

cs.LG2022★ 1 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.CV2022★ 17 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.CV2022★ 2 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…