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Motion Estimation

Motion Estimation is used to determine the block-wise or pixel-wise motion vectors between two frames.

Source: MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and Enhancement

Papers

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Showing 601–625 of 741 papers

TitleStatusHype
Variational Approach for Capsule Video Frame InterpolationCode0
Asymmetric Bilateral Phase Correlation for Optical Flow Estimation in the Frequency Domain—0
Compressed Sensing Plus Motion (CS+M): A New Perspective for Improving Undersampled MR Image Reconstruction—0
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Frame Interpolation and EnhancementCode0
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and EnhancementCode0
CNN-SVO: Improving the Mapping in Semi-Direct Visual Odometry Using Single-Image Depth PredictionCode0
Visual Object Tracking based on Adaptive Siamese and Motion Estimation Network—0
End-to-End Learning of Video Compression Using Spatio-Temporal Autoencoders—0
Deep Reinforcement Learning with Iterative Shift for Visual Tracking—0
Rolling Shutter Pose and Ego-motion Estimation using Shape-from-Template—0
Supervising the new with the old: learning SFM from SFM—0
A Deeper Insight into the UnDEMoN: Unsupervised Deep Network for Depth and Ego-Motion Estimation—0
R^3-Net: A Deep Network for Multi-oriented Vehicle Detection in Aerial Images and Videos—0
The Double Sphere Camera ModelCode0
Real-Time 2D-3D Deformable Registration with Deep Learning and Application to Lung Radiotherapy Targeting—0
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs—0
Learning-based Regularization for Cardiac Strain Analysis with Ability for Domain Adaptation—0
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry—0
Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving—0
Weakly Supervised Deep Recurrent Neural Networks for Basic Dance Step GenerationCode0
Metric-Driven Learning of Correspondence Weighting for 2-D/3-D Image Registration—0
Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image SequencesCode0
PointFlowNet: Learning Representations for Rigid Motion Estimation from Point Clouds—0
Tracking Multiple Objects Outside the Line of Sight Using Speckle Imaging—0
Rolling Shutter and Radial Distortion Are Features for High Frame Rate Multi-Camera Tracking—0
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