SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 601–625 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
Show:102550
← PrevPage 25 of 30Next →

No leaderboard results yet.