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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 226250 of 741 papers

TitleStatusHype
Attribute-Driven Spontaneous Motion in Unpaired Image TranslationCode0
Estimating articulatory movements in speech production with transformer networksCode0
CNN-SVO: Improving the Mapping in Semi-Direct Visual Odometry Using Single-Image Depth PredictionCode0
Estimating Head Motion from MR-ImagesCode0
LOAM: Lidar Odometry and Mapping in Real-TimeCode0
Deep motion estimation for parallel inter-frame prediction in video compressionCode0
Deep Motion Blind Video StabilizationCode0
EVDodgeNet: Deep Dynamic Obstacle Dodging with Event CamerasCode0
LAPNet: Non-rigid Registration derived in k-space for Magnetic Resonance ImagingCode0
Learning Dynamic Point Cloud Compression via Hierarchical Inter-frame Block MatchingCode0
A Numerical Framework for Efficient Motion Estimation on Evolving Sphere-Like Surfaces based on Brightness and Mass Conservation LawsCode0
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion SegmentationCode0
Learning to Compress Videos without Computing MotionCode0
Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image SequencesCode0
Deep Homography Estimation in Dynamic Surgical Scenes for Laparoscopic Camera Motion ExtractionCode0
Joint 3D Shape and Motion Estimation from Rolling Shutter Light-Field ImagesCode0
DeepCalib: a deep learning approach for automatic intrinsic calibration of wide field-of-view camerasCode0
Iterative Event-based Motion Segmentation by Variational Contrast MaximizationCode0
Decomposition of Optical Flow on the SphereCode0
IBVC: Interpolation-driven B-frame Video CompressionCode0
HP-GAN: Probabilistic 3D human motion prediction via GANCode0
Highly efficient non-rigid registration in k-space with application to cardiac Magnetic Resonance ImagingCode0
General Planar Motion from a Pair of 3D CorrespondencesCode0
GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera PoseCode0
A Deep Learning Framework for Assessing Physical Rehabilitation ExercisesCode0
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