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
Most implemented papers
Digging Into Self-Supervised Monocular Depth Estimation
Per-pixel ground-truth depth data is challenging to acquire at scale.
Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos
Models and examples built with TensorFlow
The Double Sphere Camera Model
We evaluate the model using a calibration dataset with several different lenses and compare the models using the metrics that are relevant for Visual Odometry, i. e., reprojection error, as well as computation time for projection and unprojection functions and their Jacobians.
On human motion prediction using recurrent neural networks
una-dinosauria/human-motion-prediction
•
•
CVPR 2017
Human motion modelling is a classical problem at the intersection of graphics and computer vision, with applications spanning human-computer interaction, motion synthesis, and motion prediction for virtual and augmented reality.
Visual-Inertial Mapping with Non-Linear Factor Recovery
We reconstruct a set of non-linear factors that make an optimal approximation of the information on the trajectory accumulated by VIO.
DeepVO: Towards End-to-End Visual Odometry with Deep Recurrent Convolutional Neural Networks
ChiWeiHsiao/DeepVO-pytorch
•
•
This paper presents a novel end-to-end framework for monocular VO by using deep Recurrent Convolutional Neural Networks (RCNNs).
FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation
m-tassano/fastdvdnet
•
•
CVPR 2020
In this paper, we propose a state-of-the-art video denoising algorithm based on a convolutional neural network architecture.
Video Enhancement with Task-Oriented Flow
Many video enhancement algorithms rely on optical flow to register frames in a video sequence.
DeepPhys: Video-Based Physiological Measurement Using Convolutional Attention Networks
terbed/Deep-rPPG
•
•
ECCV 2018
Non-contact video-based physiological measurement has many applications in health care and human-computer interaction.
Castle in the Sky: Dynamic Sky Replacement and Harmonization in Videos
jiupinjia/SkyAR
•
•
This paper proposes a vision-based method for video sky replacement and harmonization, which can automatically generate realistic and dramatic sky backgrounds in videos with controllable styles.
