Motion Estimation

88 papers with code • 0 benchmarks • 8 datasets

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

Greatest papers with code

Castle in the Sky: Dynamic Sky Replacement and Harmonization in Videos

jiupinjia/SkyAR 22 Oct 2020

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.

Motion Estimation

Unsupervised Learning of Depth and Ego-Motion from Video

tinghuiz/SfMLearner CVPR 2017

We present an unsupervised learning framework for the task of monocular depth and camera motion estimation from unstructured video sequences.

Depth And Camera Motion Motion Estimation +1

Globally Optimal Contrast Maximisation for Event-based Motion Estimation

uzh-rpg/event-based_vision_resources CVPR 2020

To alleviate this weakness, we propose a new globally optimal event-based motion estimation algorithm.

Motion Estimation

Event-based Star Tracking via Multiresolution Progressive Hough Transforms

uzh-rpg/event-based_vision_resources 19 Jun 2019

A recent alternative is to use event sensors, which could enable more energy efficient and faster star trackers.

Motion Estimation

Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motion

TRI-ML/packnet-sfm 15 Aug 2020

Self-supervised learning has emerged as a powerful tool for depth and ego-motion estimation, leading to state-of-the-art results on benchmark datasets.

Depth Estimation Motion Estimation +2

GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose

yzcjtr/GeoNet CVPR 2018

We propose GeoNet, a jointly unsupervised learning framework for monocular depth, optical flow and ego-motion estimation from videos.

Image Reconstruction Motion Estimation +1

QuaterNet: A Quaternion-based Recurrent Model for Human Motion

facebookresearch/QuaterNet 16 May 2018

Deep learning for predicting or generating 3D human pose sequences is an active research area.

3D Human Pose Estimation Motion Estimation

On human motion prediction using recurrent neural networks

facebookresearch/QuaterNet 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.

Human motion prediction Motion Estimation +2