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Found 8 papers, 3 papers with code
BirdNeRF: Fast Neural Reconstruction of Large-Scale Scenes From Aerial Imagery
In this study, we introduce BirdNeRF, an adaptation of Neural Radiance Fields (NeRF) designed specifically for reconstructing large-scale scenes using aerial imagery.
DFR: Depth from Rotation by Uncalibrated Image Rectification with Latitudinal Motion Assumption
Despite the increasing prevalence of rotating-style capture (e. g., surveillance cameras), conventional stereo rectification techniques frequently fail due to the rotation-dominant motion and small baseline between views.
Application of attention-based Siamese composite neural network in medical image recognition
Aiming at the problem of few-shot samples, a Siamese neural network suitable for classification model is proposed.
Towards Nonlinear-Motion-Aware and Occlusion-Robust Rolling Shutter Correction
This paper addresses the problem of rolling shutter correction in complex nonlinear and dynamic scenes with extreme occlusion.
Revisiting Rolling Shutter Bundle Adjustment: Toward Accurate and Fast Solution
We propose a robust and fast bundle adjustment solution that estimates the 6-DoF pose of the camera and the geometry of the environment based on measurements from a rolling shutter (RS) camera.
FEC: Fast Euclidean Clustering for Point Cloud Segmentation
Segmentation from point cloud data is essential in many applications such as remote sensing, mobile robots, or autonomous cars.
Rolling Shutter Pose and Ego-motion Estimation using Shape-from-Template
Once the virtual deformations have been recovered using SfT, the camera pose and ego-motion are computed by registering the deformed scene on the original template.
A Robust Method for Strong Rolling Shutter Effects Correction Using Lines With Automatic Feature Selection
We present a robust method which compensates RS distortions in a single image using a set of image curves, basing on the knowledge that they correspond to 3D straight lines.
