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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
Digital Twin-Assisted Cooperative Driving at Non-Signalized Intersections—0
DINO-VO: A Feature-based Visual Odometry Leveraging a Visual Foundation Model—0
Directional Primitives for Uncertainty-Aware Motion Estimation in Urban Environments—0
Direct Structure Estimation for 3D Reconstruction—0
Divergence-Based Adaptive Extreme Video Completion—0
DO3D: Self-supervised Learning of Decomposed Object-aware 3D Motion and Depth from Monocular Videos—0
Do As I Do: Transferring Human Motion and Appearance between Monocular Videos with Spatial and Temporal Constraints—0
Drift Reduction for Monocular Visual Odometry of Intelligent Vehicles using Feedforward Neural Networks—0
Dynamic Coronary Roadmapping via Catheter Tip Tracking in X-ray Fluoroscopy with Deep Learning Based Bayesian Filtering—0
DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction—0
DynPL-SVO: A Robust Stereo Visual Odometry for Dynamic Scenes—0
Efficient and Robust Registration on the 3D Special Euclidean Group—0
Efficient Computation of Relative Pose for Multi-Camera Systems—0
Efficient Globally-Optimal Correspondence-Less Visual Odometry for Planar Ground Vehicles—0
Efficient Video Neural Network Processing Based on Motion Estimation—0
EgoCast: Forecasting Egocentric Human Pose in the Wild—0
EgoHDM: An Online Egocentric-Inertial Human Motion Capture, Localization, and Dense Mapping System—0
Ego-Motion Estimation and Dynamic Motion Separation from 3D Point Clouds for Accumulating Data and Improving 3D Object Detection—0
EMoTive: Event-guided Trajectory Modeling for 3D Motion Estimation—0
EMR-MSF: Self-Supervised Recurrent Monocular Scene Flow Exploiting Ego-Motion Rigidity—0
End-to-end Learning of Object Motion Estimation from Retinal Events for Event-based Object Tracking—0
End-to-End Learning of Video Compression Using Spatio-Temporal Autoencoders—0
End-to-End Rate-Distortion Optimization for Bi-Directional Learned Video Compression—0
End-To-End Trainable Video Super-Resolution Based on a New Mechanism for Implicit Motion Estimation and Compensation—0
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs—0
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