most citedDynamic Refinement Network for Oriented and Densely Packed Object Detection

14 citations · 34 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV20208 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.CV20202 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.CV202014 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.CV20203 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…

cs.CV20197 cited

Revisiting Image Aesthetic Assessment via Self-Supervised Feature Learning

Kekai Sheng, Weiming Dong, Menglei Chai +6

Visual aesthetic assessment has been an active research field for decades. Although latest methods have achieved promising performance on benchmark datasets, they typically rely on…