22 citations · 29 across the 13 of their papers we have counts for
13 papers
SNAP: Towards Segmenting Anything in Any Point Cloud
Aniket Gupta, Hanhui Wang, Charles Saunders +3
Interactive 3D point cloud segmentation enables efficient annotation of complex 3D scenes through user-guided prompts. However, current approaches are typically restricted in scope…
A Certifably Correct Algorithm for Generalized Robot-World and Hand-Eye Calibration
Emmett Wise, Pushyami Kaveti, Qilong Chen +5
Automatic extrinsic sensor calibration is a fundamental problem for multi-sensor platforms. Reliable and general-purpose solutions should be computationally efficient, require few…
Enhancing Situational Awareness in Underwater Robotics with Multi-modal Spatial Perception
Pushyami Kaveti, Ambjorn Grimsrud Waldum, Hanumant Singh +1
Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles (ROVs) demand robust spatial perception capabilities, including Simultaneous Localization and Mapping (SLAM), t…
NeuFlow v2: Push High-Efficiency Optical Flow To the Limit
Zhiyong Zhang, Aniket Gupta, Huaizu Jiang +1
Real-time high-accuracy optical flow estimation is critical for a variety of real-world robotic applications. However, current learning-based methods often struggle to balance accu…
Towards Long Term SLAM on Thermal Imagery
Colin Keil, Aniket Gupta, Pushyami Kaveti +1
Visual SLAM with thermal imagery, and other low contrast visually degraded environments such as underwater, or in areas dominated by snow and ice, remain a difficult problem for ma…
NeuFlow: Real-time, High-accuracy Optical Flow Estimation on Robots Using Edge Devices
Zhiyong Zhang, Huaizu Jiang, Hanumant Singh
Real-time high-accuracy optical flow estimation is a crucial component in various applications, including localization and mapping in robotics, object tracking, and activity recogn…
OASIS: Optimal Arrangements for Sensing in SLAM
Pushyami Kaveti, Matthew Giamou, Hanumant Singh +1
The number and arrangement of sensors on mobile robot dramatically influence its perception capabilities. Ensuring that sensors are mounted in a manner that enables accurate detect…
A Strong Baseline for Point Cloud Registration via Direct Superpoints Matching
Aniket Gupta, Yiming Xie, Hanumant Singh +1
Deep neural networks endow the downsampled superpoints with highly discriminative feature representations. Previous dominant point cloud registration approaches match these feature…
Challenges of Indoor SLAM: A multi-modal multi-floor dataset for SLAM evaluation
Pushyami Kaveti, Aniket Gupta, Dennis Giaya +5
Robustness in Simultaneous Localization and Mapping (SLAM) remains one of the key challenges for the real-world deployment of autonomous systems. SLAM research has seen significant…
Bridging the Domain Gap between Synthetic and Real-World Data for Autonomous Driving
Xiangyu Bai, Yedi Luo, Le Jiang +4
Modern autonomous systems require extensive testing to ensure reliability and build trust in ground vehicles. However, testing these systems in the real-world is challenging due to…
Temporal-controlled Frame Swap for Generating High-Fidelity Stereo Driving Data for Autonomy Analysis
Yedi Luo, Xiangyu Bai, Le Jiang +4
This paper presents a novel approach, TeFS (Temporal-controlled Frame Swap), to generate synthetic stereo driving data for visual simultaneous localization and mapping (vSLAM) task…
Bayesian Decision Making to Localize Visual Queries in 2D
Syed Asjad, Aniket Gupta, Hanumant Singh
This report describes our approach for the EGO4D 2023 Visual Query 2D Localization Challenge. Our method aims to reduce the number of False Positives (FP) that occur because of hig…
Design and Evaluation of a Generic Visual SLAM Framework for Multi-Camera Systems
Pushyami Kaveti, Shankara Narayanan Vaidyanathan, Arvind Thamilchelvan +1
Multi-camera systems have been shown to improve the accuracy and robustness of SLAM estimates, yet state-of-the-art SLAM systems predominantly support monocular or stereo setups. T…