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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 601–650 of 741 papers

TitleStatusHype
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and EnhancementCode0
Joint Unsupervised Learning of Optical Flow and Depth by Watching Stereo VideosCode1
CNN-SVO: Improving the Mapping in Semi-Direct Visual Odometry Using Single-Image Depth PredictionCode0
Visual Object Tracking based on Adaptive Siamese and Motion Estimation Network—0
End-to-End Learning of Video Compression Using Spatio-Temporal Autoencoders—0
Supervising the new with the old: learning SFM from SFM—0
Rolling Shutter Pose and Ego-motion Estimation using Shape-from-Template—0
Deep Reinforcement Learning with Iterative Shift for Visual Tracking—0
A Deeper Insight into the UnDEMoN: Unsupervised Deep Network for Depth and Ego-Motion Estimation—0
R^3-Net: A Deep Network for Multi-oriented Vehicle Detection in Aerial Images and Videos—0
The Double Sphere Camera ModelCode0
Real-Time 2D-3D Deformable Registration with Deep Learning and Application to Lung Radiotherapy Targeting—0
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs—0
Learning-based Regularization for Cardiac Strain Analysis with Ability for Domain Adaptation—0
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry—0
Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving—0
Weakly Supervised Deep Recurrent Neural Networks for Basic Dance Step GenerationCode0
Metric-Driven Learning of Correspondence Weighting for 2-D/3-D Image Registration—0
Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image SequencesCode0
PointFlowNet: Learning Representations for Rigid Motion Estimation from Point Clouds—0
Digging Into Self-Supervised Monocular Depth EstimationCode1
Rolling Shutter and Radial Distortion Are Features for High Frame Rate Multi-Camera Tracking—0
Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion CompensationCode0
Tracking Multiple Objects Outside the Line of Sight Using Speckle Imaging—0
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion SegmentationCode0
DeepPhys: Video-Based Physiological Measurement Using Convolutional Attention NetworksCode1
Recurrent Neural Network for Learning DenseDepth and Ego-Motion from Video—0
Joint direct estimation of 3D geometry and 3D motion using spatio temporal gradients—0
QuaterNet: A Quaternion-based Recurrent Model for Human MotionCode0
Layered Optical Flow Estimation Using a Deep Neural Network with a Soft Mask—0
A Numerical Framework for Efficient Motion Estimation on Evolving Sphere-Like Surfaces based on Brightness and Mass Conservation LawsCode0
Evolution of Visual Odometry Techniques—0
Superframes, A Temporal Video Segmentation—0
SpatioTemporal Feature Integration and Model Fusion for Full Reference Video Quality AssessmentCode0
3D Fluid Flow Estimation with Integrated Particle ReconstructionCode0
Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Cars—0
Vibration-Based Damage Detection in Wind Turbine Blades using Phase-Based Motion Estimation and Motion Magnification—0
Adversarial Framework for Unsupervised Learning of Motion Dynamics in Videos—0
EVA^2: Exploiting Temporal Redundancy in Live Computer Vision—0
A Perceptual Based Motion Compensation Technique for Video Coding—0
Exploring the Distributed Video Coding in a Quality Assessment Context—0
GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera PoseCode0
Real-Time Deep Learning Method for Abandoned Luggage Detection in Video—0
Five-point Fundamental Matrix Estimation for Uncalibrated Cameras—0
Fast Piecewise-Affine Motion Estimation Without Segmentation—0
Learning to Segment Moving Objects—0
HP-GAN: Probabilistic 3D human motion prediction via GANCode0
Video Enhancement with Task-Oriented FlowCode1
Bounding Boxes, Segmentations and Object Coordinates: How Important Is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?—0
DeepVO: Towards End-to-End Visual Odometry with Deep Recurrent Convolutional Neural NetworksCode0
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