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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

Showing 526550 of 741 papers

TitleStatusHype
A Hybrid Compact Neural Architecture for Visual Place RecognitionCode0
AlignNet-3D: Fast Point Cloud Registration of Partially Observed ObjectsCode0
Image Quality Assessment for Rigid Motion Compensation0
Two Stream Networks for Self-Supervised Ego-Motion Estimation0
1-point RANSAC for Circular Motion Estimation in Computed Tomography (CT)0
SynDeMo: Synergistic Deep Feature Alignment for Joint Learning of Depth and Ego-Motion0
SME-Net: Sparse Motion Estimation for Parametric Video Prediction Through Reinforcement LearningCode0
ClusterSLAM: A SLAM Backend for Simultaneous Rigid Body Clustering and Motion Estimation0
Instance-Level Future Motion Estimation in a Single Image Based on Ordinal Regression0
Progressive Fusion Video Super-Resolution Network via Exploiting Non-Local Spatio-Temporal CorrelationsCode0
X-ray and Visible Spectra Circular Motion Images DatasetCode0
Rank Constrained Diffeomorphic Density Motion Estimation for Respiratory Correlated Computed Tomography0
Robust Monocular Edge Visual Odometry through Coarse-to-Fine Data Association0
Agent Prioritization for Autonomous Navigation0
Learning Residual Flow as Dynamic Motion from Stereo Videos0
Milli-RIO: Ego-Motion Estimation with Millimetre-Wave Radar and Inertial Measurement Unit Sensor0
Pose Estimation for Ground Robots: On Manifold Representation, Integration, Re-Parameterization, and Optimization0
Data-driven simulation for general purpose multibody dynamics using deep neural networks0
Self-supervised Recurrent Neural Network for 4D Abdominal and In-utero MR Imaging0
Mocycle-GAN: Unpaired Video-to-Video Translation0
Joint Motion Estimation and Segmentation from Undersampled Cardiac MR Image0
DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction0
Unsupervised Learning of Depth and Deep Representation for Visual Odometry from Monocular Videos in a Metric Space0
Real Time Visual Tracking using Spatial-Aware Temporal Aggregation NetworkCode0
Only Time Can Tell: Discovering Temporal Data for Temporal Modeling0
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