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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 451–500 of 741 papers

TitleStatusHype
Anatomy-Aware Cardiac Motion Estimation—0
Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motionCode2
Left Ventricular Wall Motion Estimation by Active Polynomials for Acute Myocardial Infarction Detection—0
End-to-End Rate-Distortion Optimization for Bi-Directional Learned Video Compression—0
Polarized Optical-Flow Gyroscope—0
BMBC: Bilateral Motion Estimation with Bilateral Cost Volume for Video InterpolationCode1
Entropy Minimisation Framework for Event-based Vision Model EstimationCode1
Robust Ego and Object 6-DoF Motion Estimation and TrackingCode1
Perpetual Motion: Generating Unbounded Human Motion—0
Crowdsourced 3D Mapping: A Combined Multi-View Geometry and Self-Supervised Learning ApproachCode1
Using modern motion estimation algorithms in existing video codecs—0
Minimal Cases for Computing the Generalized Relative Pose using Affine Correspondences—0
BMBC:Bilateral Motion Estimation with Bilateral Cost Volume for Video InterpolationCode1
Real-time Dense Reconstruction of Tissue Surface from Stereo Optical Video—0
Inertial Sensing Meets Artificial Intelligence: Opportunity or Challenge?—0
Monitoring of Critical Infrastructures by Micro-Motion Estimation: the Mosul Dam Destabilization—0
Patient-Specific Domain Adaptation for Fast Optical Flow Based on Teacher-Student Knowledge Transfer—0
IMU Preintegrated Features for Efficient Deep Inertial Odometry—0
Directional Primitives for Uncertainty-Aware Motion Estimation in Urban Environments—0
A Multi-spectral Dataset for Evaluating Motion Estimation SystemsCode1
Motion Pyramid Networks for Accurate and Efficient Cardiac Motion Estimation—0
Appearance Learning for Image-based Motion Estimation in Tomography—0
Multiple Video Frame Interpolation via Enhanced Deformable Separable ConvolutionCode1
Adaptively Meshed Video Stabilization—0
Semantics-Driven Unsupervised Learning for Monocular Depth and Ego-Motion Estimation—0
Deep Shutter Unrolling NetworkCode1
Self-Learning Video Rain Streak Removal: When Cyclic Consistency Meets Temporal CorrespondenceCode1
Patch based Colour Transfer using SIFT Flow—0
DeepFaceFlow: In-the-wild Dense 3D Facial Motion EstimationCode1
Taskology: Utilizing Task Relations at Scale—0
Vid2Curve: Simultaneous Camera Motion Estimation and Thin Structure Reconstruction from an RGB VideoCode1
Streaming Object Detection for 3-D Point Clouds—0
Tamed Warping Network for High-Resolution Semantic Video Segmentation—0
Deep Orientation Uncertainty Learning based on a Bingham LossCode1
Self-Supervised Attention Learning for Depth and Ego-motion Estimation—0
Spatio-Temporal Deep Learning Methods for Motion Estimation Using 4D OCT Image Data—0
A Deep Learning Approach for Motion Forecasting Using 4D OCT Data—0
Divergence-Based Adaptive Extreme Video Completion—0
Object-centered Fourier Motion Estimation and Segment-Transformation PredictionCode0
Optical Flow Estimation in the Deep Learning Age—0
Channel Attention Is All You Need for Video Frame InterpolationCode1
Minimal Solvers for Indoor UAV PositioningCode0
FlowFusion: Dynamic Dense RGB-D SLAM Based on Optical Flow—0
Maximum Likelihood Speed Estimation of Moving Objects in Video Signals—0
Deep Blind Video Super-resolutionCode1
FOAL: Fast Online Adaptive Learning for Cardiac Motion Estimation—0
DiPE: Deeper into Photometric Errors for Unsupervised Learning of Depth and Ego-motion from Monocular VideosCode1
MVP: Unified Motion and Visual Self-Supervised Learning for Large-Scale Robotic NavigationCode1
Unsupervised Learning of Depth, Optical Flow and Pose with Occlusion from 3D GeometryCode1
Joint Unsupervised Learning of Optical Flow and Egomotion with Bi-Level Optimization—0
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