Video super-resolution based on deep learning: a comprehensive survey
Video super-resolution (VSR) is reconstructing high-resolution videos from low resolution
ones. Recently, the VSR methods based on deep neural networks have made great …
ones. Recently, the VSR methods based on deep neural networks have made great …
[HTML][HTML] An overview to visual odometry and visual SLAM: Applications to mobile robotics
K Yousif, A Bab-Hadiashar… - Intelligent Industrial …, 2015 - Springer
This paper is intended to pave the way for new researchers in the field of robotics and
autonomous systems, particularly those who are interested in robot localization and …
autonomous systems, particularly those who are interested in robot localization and …
Unifying flow, stereo and depth estimation
We present a unified formulation and model for three motion and 3D perception tasks:
optical flow, rectified stereo matching and unrectified stereo depth estimation from posed …
optical flow, rectified stereo matching and unrectified stereo depth estimation from posed …
Tdan: Temporally-deformable alignment network for video super-resolution
Video super-resolution (VSR) aims to restore a photo-realistic high-resolution (HR) video
frame from both its corresponding low-resolution (LR) frame (reference frame) and multiple …
frame from both its corresponding low-resolution (LR) frame (reference frame) and multiple …
Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume
We present a compact but effective CNN model for optical flow, called PWC-Net. PWC-Net
has been designed according to simple and well-established principles: pyramidal …
has been designed according to simple and well-established principles: pyramidal …
The surprising effectiveness of diffusion models for optical flow and monocular depth estimation
S Saxena, C Herrmann, J Hur, A Kar… - Advances in …, 2024 - proceedings.neurips.cc
Denoising diffusion probabilistic models have transformed image generation with their
impressive fidelity and diversity. We show that they also excel in estimating optical flow and …
impressive fidelity and diversity. We show that they also excel in estimating optical flow and …
Global matching with overlapping attention for optical flow estimation
Optical flow estimation is a fundamental task in computer vision. Recent direct-regression
methods using deep neural networks achieve remarkable performance improvement …
methods using deep neural networks achieve remarkable performance improvement …
Super slomo: High quality estimation of multiple intermediate frames for video interpolation
Given two consecutive frames, video interpolation aims at generating intermediate frame (s)
to form both spatially and temporally coherent video sequences. While most existing …
to form both spatially and temporally coherent video sequences. While most existing …
Video frame interpolation via adaptive separable convolution
Standard video frame interpolation methods first estimate optical flow between input frames
and then synthesize an intermediate frame guided by motion. Recent approaches merge …
and then synthesize an intermediate frame guided by motion. Recent approaches merge …