[HTML][HTML] Estimating optical flow: A comprehensive review of the state of the art
Optical flow estimation is a crucial task in computer vision that provides low-level motion
information. Despite recent advances, real-world applications still present significant …
information. Despite recent advances, real-world applications still present significant …
Video enhancement with task-oriented flow
Many video enhancement algorithms rely on optical flow to register frames in a video
sequence. Precise flow estimation is however intractable; and optical flow itself is often a …
sequence. Precise flow estimation is however intractable; and optical flow itself is often a …
Frame-recurrent video super-resolution
MSM Sajjadi, R Vemulapalli… - Proceedings of the IEEE …, 2018 - openaccess.thecvf.com
Recent advances in video super-resolution have shown that convolutional neural networks
combined with motion compensation are able to merge information from multiple low …
combined with motion compensation are able to merge information from multiple low …
MFQE 2.0: A new approach for multi-frame quality enhancement on compressed video
The past few years have witnessed great success in applying deep learning to enhance the
quality of compressed image/video. The existing approaches mainly focus on enhancing the …
quality of compressed image/video. The existing approaches mainly focus on enhancing the …
Multi-frame quality enhancement for compressed video
The past few years have witnessed great success in applying deep learning to enhance the
quality of compressed image/video. The existing approaches mainly focus on enhancing the …
quality of compressed image/video. The existing approaches mainly focus on enhancing the …
Deep video super-resolution using HR optical flow estimation
Video super-resolution (SR) aims at generating a sequence of high-resolution (HR) frames
with plausible and temporally consistent details from their low-resolution (LR) counterparts …
with plausible and temporally consistent details from their low-resolution (LR) counterparts …
Generative adversarial networks and perceptual losses for video super-resolution
Video super-resolution (VSR) has become one of the most critical problems in video
processing. In the deep learning literature, recent works have shown the benefits of using …
processing. In the deep learning literature, recent works have shown the benefits of using …
A deep learning approach for multi-frame in-loop filter of HEVC
An extensive study on the in-loop filter has been proposed for a high efficiency video coding
(HEVC) standard to reduce compression artifacts, thus improving coding efficiency …
(HEVC) standard to reduce compression artifacts, thus improving coding efficiency …
Spatio-temporal transformer network for video restoration
State-of-the-art video restoration methods integrate optical flow estimation networks to utilize
temporal information. However, these networks typically consider only a pair of consecutive …
temporal information. However, these networks typically consider only a pair of consecutive …
A survey of variational and CNN-based optical flow techniques
Dense motion estimations obtained from optical flow techniques play a significant role in
many image processing and computer vision tasks. Remarkable progress has been made in …
many image processing and computer vision tasks. Remarkable progress has been made in …