Motion Estimation
209 papers with code • 0 benchmarks • 10 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
Retinal Microsurgery
Headcam
VBR
Latest papers with no code
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.
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.
Mocap Everyone Everywhere: Lightweight Motion Capture With Smartwatches and a Head-Mounted Camera
We present a lightweight and affordable motion capture method based on two smartwatches and a head-mounted camera.
HMP: Hand Motion Priors for Pose and Shape Estimation from Video
Therefore, we develop a generative motion prior specific for hands, trained on the AMASS dataset which features diverse and high-quality hand motions.
Video Frame Interpolation with Region-Distinguishable Priors from SAM
In existing Video Frame Interpolation (VFI) approaches, the motion estimation between neighboring frames plays a crucial role.
SISMIK for brain MRI: Deep-learning-based motion estimation and model-based motion correction in k-space
We propose a retrospective method for motion quantification and correction to tackle the problem of in-plane rigid-body motion, apt for classical 2D Spin-Echo scans of the brain, which are regularly used in clinical practice.
Correspondences of the Third Kind: Camera Pose Estimation from Object Reflection
In this paper, we introduce correspondences of the third kind we call reflection correspondences and show that they can help estimate camera pose by just looking at objects without relying on the background.
MaskFlow: Object-Aware Motion Estimation
We introduce a novel motion estimation method, MaskFlow, that is capable of estimating accurate motion fields, even in very challenging cases with small objects, large displacements and drastic appearance changes.
