Motion Compensation

33 papers with code • 0 benchmarks • 1 datasets

This task has no description! Would you like to contribute one?

Greatest papers with code

Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation

thunil/TecoGAN 23 Nov 2018

Additionally, we propose a first set of metrics to quantitatively evaluate the accuracy as well as the perceptual quality of the temporal evolution.

Image Super-Resolution Motion Compensation +3

Tracking without bells and whistles

phil-bergmann/tracking_wo_bnw ICCV 2019

Therefore, we motivate our approach as a new tracking paradigm and point out promising future research directions.

Motion Compensation motion prediction +1

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.

Denoising Motion Compensation +2

Detail-revealing Deep Video Super-resolution

jiangsutx/SPMC_VideoSR ICCV 2017

In this paper, we show that proper frame alignment and motion compensation is crucial for achieving high quality results.

Image Super-Resolution Motion Compensation +1

Deformable 3D Convolution for Video Super-Resolution

XinyiYing/D3Dnet 6 Apr 2020

In this paper, we propose a deformable 3D convolution network (D3Dnet) to incorporate spatio-temporal information from both spatial and temporal dimensions for video SR.

Motion Compensation Video Super-Resolution

Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation

yhjo09/VSR-DUF CVPR 2018

We propose a novel end-to-end deep neural network that generates dynamic upsampling filters and a residual image, which are computed depending on the local spatio-temporal neighborhood of each pixel to avoid explicit motion compensation.

Data Augmentation Motion Compensation +2

Learning for Video Super-Resolution through HR Optical Flow Estimation

LongguangWang/SOF-VSR 23 Sep 2018

Extensive experiments demonstrate that HR optical flows provide more accurate correspondences than their LR counterparts and improve both accuracy and consistency performance.

Motion Compensation Optical Flow Estimation +1

Progressive Fusion Video Super-Resolution Network via Exploiting Non-Local Spatio-Temporal Correlations

psychopa4/PFNL ICCV 2019

Most previous fusion strategies either fail to fully utilize temporal information or cost too much time, and how to effectively fuse temporal information from consecutive frames plays an important role in video super-resolution (SR).

Motion Compensation Motion Estimation +1