1 citations · 2 across the 5 of their papers we have counts for
5 papers
DGGAN: Degradation Guided Generative Adversarial Network for Real-time Endoscopic Video Enhancement
Handing Xu, Zhenguo Nie, Tairan Peng +2
Endoscopic surgery relies on intraoperative video, making image quality a decisive factor for surgical safety and efficacy. Yet, endoscopic videos are often degraded by uneven illu…
Rethinking Rotation-Invariant Recognition of Fine-grained Shapes from the Perspective of Contour Points
Yanjie Xu, Handing Xu, Tianmu Wang +3
Rotation-invariant recognition of shapes is a common challenge in computer vision. Recent approaches have significantly improved the accuracy of rotation-invariant recognition by e…
UNeR3D: Versatile and Scalable 3D RGB Point Cloud Generation from 2D Images in Unsupervised Reconstruction
Hongbin Lin, Juangui Xu, Qingfeng Xu +5
In the realm of 3D reconstruction from 2D images, a persisting challenge is to achieve high-precision reconstructions devoid of 3D Ground Truth data reliance. We present UNeR3D, a…
SuperMeshing: A New Deep Learning Architecture for Increasing the Mesh Density of Metal Forming Stress Field with Attention Mechanism and Perceptual Features
Qingfeng Xu, Zhenguo Nie, Handing Xu +2
In stress field analysis, the finite element analysis is a crucial approach, in which the mesh-density has a significant impact on the results. High mesh density usually contribute…
SuperMeshing: A Novel Method for Boosting the Mesh Density in Numerical Computation within 2D Domain
Handing Xu, Zhenguo Nie, Qingfeng Xu +1
Due to the limit of mesh density, the improvement of the spatial precision of numerical computation always leads to a decrease in computing efficiency. Aiming at this inability of…