1 citations · 1 across the 4 of their papers we have counts for
5 papers
Probing the 3D Object-Level Understanding of Pre-Trained Detection Transformers
Robin Kim, Colin Samplawski, Benjamin M. Marlin
Detection transformer models, including DETR and its extensions, learn to output a set of object-level embeddings that can be simultaneously decoded into 2D bounding boxes and clas…
Temporally Multi-Scale Sparse Self-Attention for Physical Activity Data Imputation
Hui Wei, Maxwell A. Xu, Colin Samplawski +3
Wearable sensors enable health researchers to continuously collect data pertaining to the physiological state of individuals in real-world settings. However, such data can be subje…
FlexLoc: Conditional Neural Networks for Zero-Shot Sensor Perspective Invariance in Object Localization with Distributed Multimodal Sensors
Jason Wu, Ziqi Wang, Xiaomin Ouyang +5
Localization is a critical technology for various applications ranging from navigation and surveillance to assisted living. Localization systems typically fuse information from sen…
GDTM: An Indoor Geospatial Tracking Dataset with Distributed Multimodal Sensors
Ho Lyun Jeong, Ziqi Wang, Colin Samplawski +6
Constantly locating moving objects, i.e., geospatial tracking, is essential for autonomous building infrastructure. Accurate and robust geospatial tracking often leverages multimod…
Heteroskedastic Geospatial Tracking with Distributed Camera Networks
Colin Samplawski, Shiwei Fang, Ziqi Wang +3
Visual object tracking has seen significant progress in recent years. However, the vast majority of this work focuses on tracking objects within the image plane of a single camera…