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    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 ...

    **anqiang Lyu, Junhui Hou in International Journal of Computer Vision (2024)

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    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 ...

    Yifan Zhang, Junhui Hou, Yixuan Yuan in International Journal of Computer Vision (2024)

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    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...

    Yifan Zhang, Qijian Zhang, Zhiyu Zhu in International Journal of Computer Vision (2023)

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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...

    Qijian Zhang, Junhui Hou, Yue Qian in International Journal of Computer Vision (2022)