13 citations · 58 across the 8 of their papers we have counts for
8 papers
FOF: Learning Fourier Occupancy Field for Monocular Real-time Human Reconstruction
Qiao Feng, Yebin Liu, Yu-Kun Lai +2
The advent of deep learning has led to significant progress in monocular human reconstruction. However, existing representations, such as parametric models, voxel grids, meshes and…
TerrainMesh: Metric-Semantic Terrain Reconstruction from Aerial Images Using Joint 2D-3D Learning
Qiaojun Feng, Nikolay Atanasov
This paper considers outdoor terrain mapping using RGB images obtained from an aerial vehicle. While feature-based localization and mapping techniques deliver real-time vehicle odo…
ELLIPSDF: Joint Object Pose and Shape Optimization with a Bi-level Ellipsoid and Signed Distance Function Description
Mo Shan, Qiaojun Feng, You-Yi Jau +1
Autonomous systems need to understand the semantics and geometry of their surroundings in order to comprehend and safely execute object-level task specifications. This paper propos…
Fully Convolutional Geometric Features for Category-level Object Alignment
Qiaojun Feng, Nikolay Atanasov
This paper focuses on pose registration of different object instances from the same category. This is required in online object mapping because object instances detected at test ti…
Localization and Mapping using Instance-specific Mesh Models
Qiaojun Feng, Yue Meng, Mo Shan +1
This paper focuses on building semantic maps, containing object poses and shapes, using a monocular camera. This is an important problem because robots need rich understanding of g…
CORSAIR: Convolutional Object Retrieval and Symmetry-AIded Registration
Tianyu Zhao, Qiaojun Feng, Sai Jadhav +1
This paper considers online object-level mapping using partial point-cloud observations obtained online in an unknown environment. We develop and approach for fully Convolutional O…
Mesh Reconstruction from Aerial Images for Outdoor Terrain Mapping Using Joint 2D-3D Learning
Qiaojun Feng, Nikolay Atanasov
This paper addresses outdoor terrain mapping using overhead images obtained from an unmanned aerial vehicle. Dense depth estimation from aerial images during flight is challenging.…
OrcVIO: Object residual constrained Visual-Inertial Odometry
Mo Shan, Vikas Dhiman, Qiaojun Feng +2
Introducing object-level semantic information into simultaneous localization and mapping (SLAM) system is critical. It not only improves the performance but also enables tasks spec…