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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 401–450 of 741 papers

TitleStatusHype
Occupancy Flow Fields for Motion Forecasting in Autonomous Driving—0
Globally-Optimal Event Camera Motion Estimation—0
Triple Motion Estimation and Frame Interpolation based on Adaptive Threshold for Frame Rate Up-Conversion—0
H4D: Human 4D Modeling by Learning Neural Compositional Representation—0
Efficient Globally-Optimal Correspondence-Less Visual Odometry for Planar Ground Vehicles—0
A modification of the conjugate direction method for motion estimation—0
Spatio-Temporal Outdoor Lighting Aggregation on Image Sequences using Transformer Networks—0
Dilated convolutional neural network-based deep reference picture generation for video compressionCode0
Real-Time Siamese Multiple Object Tracker with Enhanced ProposalsCode0
Estimation of Clinical Workload and Patient Activity using Deep Learning and Optical Flow—0
Fractional Motion Estimation for Point Cloud Compression—0
Motion Estimation and Compensation in Automotive MIMO SAR—0
Condensing a Sequence to One Informative Frame for Video Recognition—0
RigidFlow: Self-Supervised Scene Flow Learning on Point Clouds by Local Rigidity Prior—0
RCP: Recurrent Closest Point for Point CloudCode0
Adaptation and Attention for Neural Video Coding—0
Self-Supervised Camera Self-Calibration from Video—0
Learning-Based Video Coding with Joint Deep Compression and Enhancement—0
Learning Generalized Visual Odometry Using Position-Aware Optical Flow and Geometric Bundle Adjustment—0
Probabilistic Spatial Distribution Prior Based Attentional Keypoints Matching Network—0
Differential Motion Evolution for Fine-Grained Motion Deformation in Unsupervised Image Animation—0
Self-Supervised Learning of Perceptually Optimized Block Motion Estimates for Video Compression—0
Deep Homography Estimation in Dynamic Surgical Scenes for Laparoscopic Camera Motion ExtractionCode0
Physics-based Human Motion Estimation and Synthesis from Videos—0
Contact-Aware Retargeting of Skinned Motion—0
Temporally Coherent Person Matting Trained on Fake-Motion Dataset—0
GOHOME: Graph-Oriented Heatmap Output for future Motion Estimation—0
Sparse to Dense Motion Transfer for Face Image Animation—0
CSMCNet: Scalable Video Compressive Sensing Reconstruction with Interpretable Motion Estimation—0
Accelerating Markov Random Field Inference with Uncertainty Quantification—0
LAPNet: Non-rigid Registration derived in k-space for Magnetic Resonance ImagingCode0
Novel Approach To Synchronisation Of Wearable IMUs Based On Magnetometers—0
Visual Odometry with an Event Camera Using Continuous Ray Warping and Volumetric Contrast Maximization—0
3D Video Stabilization With Depth Estimation by CNN-Based Optimization—0
Feature-Level Collaboration: Joint Unsupervised Learning of Optical Flow, Stereo Depth and Camera Motion—0
Back to Event Basics: Self-Supervised Learning of Image Reconstruction for Event Cameras via Photometric Constancy—0
An Unsupervised Optical Flow Estimation For LiDAR Image Sequences—0
DeepAVO: Efficient Pose Refining with Feature Distilling for Deep Visual Odometry—0
Finding a Needle in a Haystack: Tiny Flying Object Detection in 4K Videos using a Joint Detection-and-Tracking Approach—0
Algorithmic Principles of Camera-based Respiratory Motion Extraction—0
Digital Twin-Assisted Cooperative Driving at Non-Signalized Intersections—0
Estimating articulatory movements in speech production with transformer networksCode0
Full Surround Monodepth from Multiple Cameras—0
CNN-based Cardiac Motion Extraction to Generate Deformable Geometric Left Ventricle Myocardial Models from Cine MRI—0
Revisiting Self-Supervised Monocular Depth EstimationCode0
Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling—0
Motion Estimation for Optical Coherence Elastography Using Signal Phase and Intensity—0
Fast and Accurate: Video Enhancement using Sparse Depth—0
Rigid and non-rigid motion compensation in weight-bearing cone-beam CT of the knee using (noisy) inertial measurements—0
Relying on a rate constraint to reduce Motion Estimation complexityCode0
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