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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 701–741 of 741 papers

TitleStatusHype
Contour Flow: Middle-Level Motion Estimation by Combining Motion Segmentation and Contour Alignment—0
Spatio-temporal video autoencoder with differentiable memoryCode0
Unsupervised Learning of Edges—0
Multimodal MRI Neuroimaging with Motion Compensation Based on Particle Filtering—0
Bioinspired Visual Motion EstimationCode0
Long-Range Motion Trajectories Extraction of Articulated Human Using Mesh Evolution—0
Graph-based compression of dynamic 3D point cloud sequences—0
Direct Structure Estimation for 3D Reconstruction—0
Exact Bias Correction and Covariance Estimation for Stereo Vision—0
Harmonic Exponential Families on Manifolds—0
A robust and efficient video representation for action recognition—0
Novel Super-Resolution Method Based on High Order Nonlocal-Means—0
Macroblock Classification Method for Video Applications Involving Motions—0
A Robust Point Sets Matching Method—0
Motion Estimation via Robust Decomposition with Constrained Rank—0
Concurrent Tracking of Inliers and Outliers—0
Tracking Individual Targets in High Density Crowd Scenes Analysis of a Video Recording in Hajj 2009—0
LOAM: Lidar Odometry and Mapping in Real-TimeCode0
Block matching algorithm for motion estimation based on Artificial Bee Colony (ABC)—0
Block matching algorithm based on Harmony Search optimization for motion estimation—0
Fast and Reliable Two-View Translation Estimation—0
Efficient Computation of Relative Pose for Multi-Camera Systems—0
Local Layering for Joint Motion Estimation and Occlusion Detection—0
A Minimal Solution to the Generalized Pose-and-Scale Problem—0
Motion-Compensated Coding and Frame-Rate Up-Conversion: Models and Analysis—0
Expectation-Maximization Technique and Spatial-Adaptation Applied to Pel-Recursive Motion Estimation—0
Tracking via Motion Estimation with Physically Motivated Inter-Region Constraints—0
Stable Camera Motion Estimation Using Convex Programming—0
Decomposition of Optical Flow on the SphereCode0
Optical Flow on Evolving Surfaces with Space and Time Regularisation—0
Learning to encode motion using spatio-temporal synchrony—0
Large Displacement Optical Flow from Nearest Neighbor Fields—0
Motion Estimation for Self-Driving Cars with a Generalized Camera—0
Dense Segmentation-Aware Descriptors—0
A Fully-Connected Layered Model of Foreground and Background Flow—0
Pose from Flow and Flow from Pose—0
Determining Motion Directly from Normal Flows Upon the Use of a Spherical Eye Platform—0
Optical Flow on Evolving Surfaces with an Application to the Analysis of 4D Microscopy Data—0
Functional form of motion priors in human motion perception—0
Occlusion Detection and Motion Estimation with Convex Optimization—0
Layered image motion with explicit occlusions, temporal consistency, and depth ordering—0
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