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Found 8 papers, 1 papers with code
DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection
Deep learning has achieved notable success in 3D object detection with the advent of large-scale point cloud datasets.
FaultNet: Faulty Rail-Valves Detection using Deep Learning and Computer Vision
In this paper, a multi-phase deep learning based technique is proposed to perform accurate fault detection of rail-valves.
Dense 3D Reconstruction for Visual Tunnel Inspection using Unmanned Aerial Vehicle
In this work, we design a UAV with a single rotating camera to accomplish the task.
A*3D Dataset: Towards Autonomous Driving in Challenging Environments
With the increasing global popularity of self-driving cars, there is an immediate need for challenging real-world datasets for benchmarking and training various computer vision tasks such as 3D object detection.
Feature-less Stitching of Cylindrical Tunnel
Traditional image stitching algorithms use transforms such as homography to combine different views of a scene.
Tracking objects using 3D object proposals
3D object proposals, quickly detected regions in a 3D scene that likely contain an object of interest, are an effective approach to improve the computational efficiency and accuracy of the object detection framework.
Calibration of depth cameras using denoised depth images
Depth sensing devices have created various new applications in scientific and commercial research with the advent of Microsoft Kinect and PMD (Photon Mixing Device) cameras.
Locating 3D Object Proposals: A Depth-Based Online Approach
Using efficient but robust registration enables us to combine multiple frames of a scene in near real time and generate 3D bounding boxes for potential 3D regions of interest.
