Motion Compensation
61 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Motion Compensation
RGB-DAVIS Dataset
Most implemented papers
PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI
In this paper we present a novel method for the correction of motion artifacts that are present in fetal Magnetic Resonance Imaging (MRI) scans of the whole uterus.
Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion
Our approach is attractive in challenging imaging scenarios, where significant subject motion complicates reconstruction performance of 3D volumes from 2D slice data.
Detail-revealing Deep Video Super-resolution
jiangsutx/SPMC_VideoSR
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ICCV 2017
In this paper, we show that proper frame alignment and motion compensation is crucial for achieving high quality results.
Motion Compensated Dynamic MRI Reconstruction with Local Affine Optical Flow Estimation
This paper proposes a novel framework to reconstruct the dynamic magnetic resonance images (DMRI) with motion compensation (MC).
Multi-Frame Quality Enhancement for Compressed Video
In this paper, we investigate that heavy quality fluctuation exists across compressed video frames, and thus low quality frames can be enhanced using the neighboring high quality frames, seen as Multi-Frame Quality Enhancement (MFQE).
Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation
We propose a novel end-to-end deep neural network that generates dynamic upsampling filters and a residual image, which are computed depending on the local spatio-temporal neighborhood of each pixel to avoid explicit motion compensation.
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and Enhancement
Recently, a number of data-driven frame interpolation methods based on convolutional neural networks have been proposed.
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Frame Interpolation and Enhancement
baowenbo/MEMC-Net
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arXiv 2018
In this work, we propose a motion estimation and motion compensation driven neural network for video frame interpolation.
Event-Based Motion Segmentation by Motion Compensation
In contrast to traditional cameras, whose pixels have a common exposure time, event-based cameras are novel bio-inspired sensors whose pixels work independently and asynchronously output intensity changes (called "events"), with microsecond resolution.
Focus Is All You Need: Loss Functions For Event-based Vision
The proposed loss functions allow bringing mature computer vision tools to the realm of event cameras.
