8 papers
Project SCOUT: Interceptor Drone for Perimeter Defense
Azmain Yousuf, Siwei Cai, Knut Peterson +2
The rapid proliferation of unauthorized unmanned aerial vehicles (UAVs) has created a growing need for robust, jamming-resistant counter-UAV systems for perimeter defense. This pap…
DroneDAR: Long-Range Drone Distance Estimation Using Monocular Vision and Bounding-Box Features
Knut Peterson, Zaid Mayers, David Han
Accurate distance estimation for small drones in long-range imagery is important for tracking and situational awareness, yet remains challenging due to extreme target scale variati…
LRDDv3: High-Resolution Long-Range Drone Detection Dataset with Range Information and Thermal Data
Knut Peterson, Zaid Mayers, Azmain Yousuf +5
Unmanned Aerial Vehicles (UAVs) have quickly become common in various airspaces, representing a wide range of applications from recreation flying to commercial photography and pack…
AGT-CV: An Aerial-Ground Team Cross-View Dataset for Heterogeneous Robot Teams in Unstructured Environments
Siwei Cai, Knut Peterson, Quan Tran +7
Heterogeneous air-ground robot teams combine complementary sensing modalities, mobility characteristics, and spatial viewpoints that can significantly enhance perception in complex…
Electrostatics-Inspired Surface Reconstruction (EISR): Recovering 3D Shapes as a Superposition of Poisson's PDE Solutions
Diego Patiño, Knut Peterson, Kostas Daniilidis +1
Implicit shape representation, such as SDFs, is a popular approach to recover the surface of a 3D shape as the level sets of a scalar field. Several methods approximate SDFs using…
Predicting Dynamic Map States from Limited Field-of-View Sensor Data
Knut Peterson, David Han
When autonomous systems are deployed in real-world scenarios, sensors are often subject to limited field-of-view (FOV) constraints, either naturally through system design, or throu…
ADAM: Autonomous Discovery and Annotation Model using LLMs for Context-Aware Annotations
Amirreza Rouhi, Solmaz Arezoomandan, Knut Peterson +2
Object detection models typically rely on predefined categories, limiting their ability to identify novel objects in open-world scenarios. To overcome this constraint, we introduce…
Domain-Transferred Synthetic Data Generation for Improving Monocular Depth Estimation
Seungyeop Lee, Knut Peterson, Solmaz Arezoomandan +4
A major obstacle to the development of effective monocular depth estimation algorithms is the difficulty in obtaining high-quality depth data that corresponds to collected RGB imag…