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Xi Cheng

3 accepted papers

2025

Constraint-Aware Feature Learning for Parametric Point Cloud

ICCV 2025poster

Parametric point clouds are sampled from CAD shapes and are becoming increasingly common in industrial manufacturing. Most CAD-specific deep learning methods focus on geometric features, while overlooking constraints inherent in CAD shapes. This limits their ability to discern CAD shapes with simila…

Cited by 0SourcePDFScholar
2025

Training-Free Point Cloud Recognition Based on Geometric and Semantic Information Fusion

ICASSP 2025accepted

The trend of employing training-free methods for point cloud recognition is becoming increasingly popular due to its significant reduction in computational resources and time costs. However, existing approaches are limited as they typically extract either geometric or semantic features. To address t…

Cited by 0SourceScholar
2020

Zero-Shot Image Super-Resolution with Depth Guided Internal Degradation Learning

ECCV 2020poster

In the past few years, we have witnessed the great progress of image super-resolution (SR) thanks to the power of deep learning. However, a major limitation of the current image SR approaches is that they assume a pre-determined degradation model or kernel, e.g. bicubic, controls the image degradati…

Cited by 45SourcePDFScholar