202 citations · 563 across the 65 of their papers we have counts for
10 papers · 1 filter
PKF: Probabilistic Data Association Kalman Filter for Multi-Object Tracking
Hanwen Cao, George J. Pappas, Nikolay Atanasov
In this paper, we derive a new Kalman filter with probabilistic data association between measurements and states. We formulate a variational inference problem to approximate the po…
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…
A Deep Signed Directional Distance Function for Object Shape Representation
Ehsan Zobeidi, Nikolay Atanasov
Neural networks that map 3D coordinates to signed distance function (SDF) or occupancy values have enabled high-fidelity implicit representations of object shape. This paper develo…
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.…
A spatiotemporal model with visual attention for video classification
Mo Shan, Nikolay Atanasov
High level understanding of sequential visual input is important for safe and stable autonomy, especially in localization and object detection. While traditional object classificat…
Active Deformable Part Models
Menglong Zhu, Nikolay Atanasov, George J. Pappas +1
This paper presents an active approach for part-based object detection, which optimizes the order of part filter evaluations and the time at which to stop and make a prediction. St…