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
Space-Time Video Super-resolution with Neural Operator
This paper addresses the task of space-time video super-resolution (ST-VSR).
An N-Point Linear Solver for Line and Motion Estimation with Event Cameras
To recover the full linear camera velocity we fuse observations from multiple lines with a novel velocity averaging scheme that relies on a geometrically-motivated residual, and thus solves the problem more efficiently than previous schemes which minimize an algebraic residual.
Uncertainty-Aware Deep Video Compression with Ensembles
Deep learning-based video compression is a challenging task, and many previous state-of-the-art learning-based video codecs use optical flows to exploit the temporal correlation between successive frames and then compress the residual error.
Object Segmentation-Assisted Inter Prediction for Versatile Video Coding
Moreover, segmentation mask is considered in the joint rate-distortion optimization for motion estimation and partition estimation to derive the motion vector of different regions and partition more accurately.
DO3D: Self-supervised Learning of Decomposed Object-aware 3D Motion and Depth from Monocular Videos
Our system contains a depth estimation module to predict depth, and a new decomposed object-wise 3D motion (DO3D) estimation module to predict ego-motion and 3D object motion.
Exploiting polar symmetry in designing equivariant observers for vision-based motion estimation
Accurately estimating camera motion from image sequences poses a significant challenge in computer vision and robotics.
Improved LiDAR Odometry and Mapping using Deep Semantic Segmentation and Novel Outliers Detection
In this work, we propose a novel framework for real-time LiDAR odometry and mapping based on LOAM architecture for fast moving platforms.
Explicit Motion Handling and Interactive Prompting for Video Camouflaged Object Detection
The prompt fed to the motion stream is learned by supervising optical flow in a self-supervised manner.
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.
