activity
20192026
most citedDomain Enhanced Arbitrary Image Style Transfer via Contrastive Learning

209 citations · 347 across the 45 of their papers we have counts for

collaborators
Showing 2020 · cs.CVShow all

5 papers · 2 filters

cs.CV2020★ 8 cited

Effective Label Propagation for Discriminative Semi-Supervised Domain Adaptation

Zhiyong Huang, Kekai Sheng, Weiming Dong +5

Semi-supervised domain adaptation (SSDA) methods have demonstrated great potential in large-scale image classification tasks when massive labeled data are available in the source d…

cs.CV2020

Arbitrary Video Style Transfer via Multi-Channel Correlation

Yingying Deng, Fan Tang, Weiming Dong +3

Video style transfer is getting more attention in AI community for its numerous applications such as augmented reality and animation productions. Compared with traditional image st…

cs.CV2020★ 2 cited

Improving Monocular Depth Estimation by Leveraging Structural Awareness and Complementary Datasets

Tian Chen, Shijie An, Yuan Zhang +4

Monocular depth estimation plays a crucial role in 3D recognition and understanding. One key limitation of existing approaches lies in their lack of structural information exploita…

cs.CV2020★ 14 cited

Dynamic Refinement Network for Oriented and Densely Packed Object Detection

Xingjia Pan, Yuqiang Ren, Kekai Sheng +5

Object detection has achieved remarkable progress in the past decade. However, the detection of oriented and densely packed objects remains challenging because of following inheren…

cs.CV2020★ 3 cited

Distribution Aligned Multimodal and Multi-Domain Image Stylization

Minxuan Lin, Fan Tang, Weiming Dong +3

Multimodal and multi-domain stylization are two important problems in the field of image style transfer. Currently, there are few methods that can perform both multimodal and multi…