Motion Estimation
205 papers with code • 0 benchmarks • 9 datasets
Motion Estimation is used to determine the block-wise or pixel-wise motion vectors between two frames.
Benchmarks
These leaderboards are used to track progress in Motion Estimation
Libraries
Use these libraries to find Motion Estimation models and implementationsDatasets
DDD17
PST900
SegTHOR
EV-IMO
Fisheye
Headcam
Retinal Microsurgery
Latest papers with no code
DD-VNB: A Depth-based Dual-Loop Framework for Real-time Visually Navigated Bronchoscopy
Specifically, the relative pose changes are fed into the registration process as the initial guess to boost its accuracy and speed.
OMRA: Online Motion Resolution Adaptation to Remedy Domain Shift in Learned Hierarchical B-frame Coding
To mitigate the domain shift, we present an online motion resolution adaptation (OMRA) method.
TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction
Inter-frame motion in dynamic cardiac positron emission tomography (PET) using rubidium-82 (82-Rb) myocardial perfusion imaging impacts myocardial blood flow (MBF) quantification and the diagnosis accuracy of coronary artery diseases.
MIRT: a simultaneous reconstruction and affine motion compensation technique for four dimensional computed tomography (4DCT)
In four-dimensional computed tomography (4DCT), 3D images of moving or deforming samples are reconstructed from a set of 2D projection images.
Is Registering Raw Tagged-MR Enough for Strain Estimation in the Era of Deep Learning?
This is a factor that has been overlooked in prior research on tMRI post-processing.
Spatial Decomposition and Temporal Fusion based Inter Prediction for Learned Video Compression
With the SDD-based motion model and long short-term temporal contexts fusion, our proposed learned video codec can obtain more accurate inter prediction.
Vanishing-Point-Guided Video Semantic Segmentation of Driving Scenes
The estimation of implicit cross-frame correspondences and the high computational cost have long been major challenges in video semantic segmentation (VSS) for driving scenes.
Conditional Neural Video Coding with Spatial-Temporal Super-Resolution
This document is an expanded version of a one-page abstract originally presented at the 2024 Data Compression Conference.
A gradient-based approach to fast and accurate head motion compensation in cone-beam CT
The analytic Jacobian for the backprojection operation, which is at the core of the proposed method, is made publicly available.
Dense Optical Flow Estimation Using Sparse Regularizers from Reduced Measurements
In this work, we incorporate concepts from signal sparsity into variational regularization for motion estimation.
