Search Results for author:
Found 24 papers, 12 papers with code
Visual Detection of Diver Attentiveness for Underwater Human-Robot Interaction
Many underwater tasks, such as cable-and-wreckage inspection, search-and-rescue, benefit from robust human-robot interaction (HRI) capabilities.
Robotic Detection of a Human-Comprehensible Gestural Language for Underwater Multi-Human-Robot Collaboration
Our experimental evaluations, both in simulation and in closed-water robot trials, demonstrate that the proposed RRCommNet architecture is able to decipher gesture-based messages with an average accuracy of 88-94% on simulated data, 73-83% on real data (depending on the version of the model used).
A Generative Approach for Detection-driven Underwater Image Enhancement
In this paper, we introduce a generative model for image enhancement specifically for improving diver detection in the underwater domain.
An Analysis of Deep Object Detectors For Diver Detection
We evaluate these networks on typical accuracy and efficiency metrics, as well as on the temporal stability of their detections.
Visual Diver Face Recognition for Underwater Human-Robot Interaction
Specifically, the proposed method is able to recognize divers underwater with faces heavily obscured by scuba masks and breathing apparatus.
SVAM: Saliency-guided Visual Attention Modeling by Autonomous Underwater Robots
This paper presents a holistic approach to saliency-guided visual attention modeling (SVAM) for use by autonomous underwater robots.
IMU-Assisted Learning of Single-View Rolling Shutter Correction
In this paper, we propose a deep neural network to predict depth and row-wise pose from a single image for rolling shutter correction.
TrashCan: A Semantically-Segmented Dataset towards Visual Detection of Marine Debris
This paper presents TrashCan, a large dataset comprised of images of underwater trash collected from a variety of sources, annotated both using bounding boxes and segmentation labels, for development of robust detectors of marine debris.
Semantic Segmentation of Underwater Imagery: Dataset and Benchmark
We also present a benchmark evaluation of state-of-the-art semantic segmentation approaches based on standard performance metrics.
Simultaneous Enhancement and Super-Resolution of Underwater Imagery for Improved Visual Perception
In this paper, we introduce and tackle the simultaneous enhancement and super-resolution (SESR) problem for underwater robot vision and provide an efficient solution for near real-time applications.
A Generative Approach Towards Improved Robotic Detection of Marine Litter
The proposed approach relies on a two-stage variational autoencoder (VAE) and a binary classifier to evaluate the generated imagery for quality and realism.
Underwater Image Super-Resolution using Deep Residual Multipliers
We present a deep residual network-based generative model for single image super-resolution (SISR) of underwater imagery for use by autonomous underwater robots.
Ranked #1 on
Image Super-Resolution
on USR-248 - 4x upscaling
A Fast and Robust Place Recognition Approach for Stereo Visual Odometry Using LiDAR Descriptors
Place recognition is a core component of Simultaneous Localization and Mapping (SLAM) algorithms.
Extending Monocular Visual Odometry to Stereo Camera Systems by Scale Optimization
This paper proposes a novel approach for extending monocular visual odometry to a stereo camera system.
Fast Underwater Image Enhancement for Improved Visual Perception
In this paper, we present a conditional generative adversarial network-based model for real-time underwater image enhancement.
Ranked #4 on
Underwater Image Restoration
on LSUI
(using extra training data)
By Land, Air, or Sea: Multi-Domain Robot Communication Via Motion
In this paper, we explore the use of motion for robot-to-human communication on three robotic platforms: the 5 degrees-of-freedom (DOF) Aqua autonomous underwater vehicle (AUV), a 3-DOF camera gimbal mounted on a Matrice 100 drone, and a 3-DOF Turtlebot2 terrestrial robot.
Robotics
DSVO: Direct Stereo Visual Odometry
This paper proposes a novel approach to stereo visual odometry without stereo matching.
Visual Diver Recognition for Underwater Human-Robot Collaboration
This paper presents an approach for autonomous underwater robots to visually detect and identify divers.
SafeDrive: Enhancing Lane Appearance for Autonomous and Assisted Driving Under Limited Visibility
SafeDrive finds lane markers in alternate imagery of the road at the vehicle's location and reconstructs a sparse 3D model of the surroundings.
Person Following by Autonomous Robots: A Categorical Overview
Different working environments and applications pose diverse challenges by adding constraints on the choice of sensors, the degree of autonomy, and dynamics of a person-following robot.
Robotics
Enhancing Underwater Imagery using Generative Adversarial Networks
Autonomous underwater vehicles (AUVs) rely on a variety of sensors - acoustic, inertial and visual - for intelligent decision making.
Ranked #3 on
Underwater Image Restoration
on LSUI
(using extra training data)
Dynamic Reconfiguration of Mission Parameters in Underwater Human-Robot Collaboration
This paper presents a real-time programming and parameter reconfiguration method for autonomous underwater robots in human-robot collaborative tasks.
Underwater Multi-Robot Convoying using Visual Tracking by Detection
We present a robust multi-robot convoying approach that relies on visual detection of the leading agent, thus enabling target following in unstructured 3-D environments.
SafeDrive: A Robust Lane Tracking System for Autonomous and Assisted Driving Under Limited Visibility
In scenarios where visual lane detection algorithms are unable to detect lane markers, the proposed approach uses location information of the vehicle to locate and access alternate imagery of the road and attempts detection on this secondary image.
