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Article
Probabilistic-Based Feature Embedding of 4-D Light Fields for Compressive Imaging and Denoising
The high-dimensional nature of the 4-D light field (LF) poses great challenges in achieving efficient and effective feature embedding, that severely impacts the performance of downstream tasks. To tackle this ...
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Article
A Comprehensive Study of the Robustness for LiDAR-Based 3D Object Detectors Against Adversarial Attacks
Recent years have witnessed significant advancements in deep learning-based 3D object detection, leading to its widespread adoption in numerous applications. As 3D object detectors become increasingly crucial ...
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Article
GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation
The inherent ambiguity in ground-truth annotations of 3D bounding boxes, caused by occlusions, signal missing, or manual annotation errors, can confuse deep 3D object detectors during training, thus deteriorat...
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Article
RegGeoNet: Learning Regular Representations for Large-Scale 3D Point Clouds
Deep learning has proven an effective tool for 3D point cloud processing. Currently, most deep set architectures are developed for sparse inputs (typically with a few thousand points), which are unable to prov...
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Chapter and Conference Paper
DRLFNet: A Dense-Connection Residual Learning Neural Network for Light Field Super Resolution
Light field records both spatial and angular information of light rays. By using light field cameras, 3D scenes can be reconstructed easily for further virtual reality applications. Limited by the sensor size,...