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RGB-based Category-level Object Pose Estimation via Decoupled Metric Scale Recovery
Jiaxin Wei, Xibin Song, Weizhe Liu +3
While showing promising results, recent RGB-D camera-based category-level object pose estimation methods have restricted applications due to the heavy reliance on depth sensors. RG…
Deep Video Restoration for Under-Display Camera
Xuanxi Chen, Tao Wang, Ziqian Shao +6
Images or videos captured by the Under-Display Camera (UDC) suffer from severe degradation, such as saturation degeneration and color shift. While restoration for UDC has been a cr…
MAVIS: Multi-Camera Augmented Visual-Inertial SLAM using SE2(3) Based Exact IMU Pre-integration
Yifu Wang, Yonhon Ng, Inkyu Sa +4
We present a novel optimization-based Visual-Inertial SLAM system designed for multiple partially overlapped camera systems, named MAVIS. Our framework fully exploits the benefits…
Unsupervised 3D Pose Estimation with Non-Rigid Structure-from-Motion Modeling
Haorui Ji, Hui Deng, Yuchao Dai +1
Most of the previous 3D human pose estimation work relied on the powerful memory capability of the network to obtain suitable 2D-3D mappings from the training data. Few works have…
View Consistent Purification for Accurate Cross-View Localization
Shan Wang, Yanhao Zhang, Akhil Perincherry +2
This paper proposes a fine-grained self-localization method for outdoor robotics that utilizes a flexible number of onboard cameras and readily accessible satellite images. The pro…
Boosting 3-DoF Ground-to-Satellite Camera Localization Accuracy via Geometry-Guided Cross-View Transformer
Yujiao Shi, Fei Wu, Akhil Perincherry +2
Image retrieval-based cross-view localization methods often lead to very coarse camera pose estimation, due to the limited sampling density of the database satellite images. In thi…
Event-guided Multi-patch Network with Self-supervision for Non-uniform Motion Deblurring
Hongguang Zhang, Limeng Zhang, Yuchao Dai +2
Contemporary deep learning multi-scale deblurring models suffer from many issues: 1) They perform poorly on non-uniformly blurred images/videos; 2) Simply increasing the model dept…