Computer vision for autonomous vehicles: Problems, datasets and state of the art
Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
A review on deep learning techniques for video prediction
S Oprea, P Martinez-Gonzalez… - … on Pattern Analysis …, 2020 - ieeexplore.ieee.org
The ability to predict, anticipate and reason about future outcomes is a key component of
intelligent decision-making systems. In light of the success of deep learning in computer …
intelligent decision-making systems. In light of the success of deep learning in computer …
Gmflow: Learning optical flow via global matching
Learning-based optical flow estimation has been dominated with the pipeline of cost volume
with convolutions for flow regression, which is inherently limited to local correlations and …
with convolutions for flow regression, which is inherently limited to local correlations 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 …
Grounding image matching in 3d with mast3r
Image Matching is a core component of all best-performing algorithms and pipelines in 3D
vision. Yet despite matching being fundamentally a 3D problem, intrinsically linked to …
vision. Yet despite matching being fundamentally a 3D problem, intrinsically linked to …
Learning to estimate hidden motions with global motion aggregation
Occlusions pose a significant challenge to optical flow algorithms that rely on local
evidences. We consider an occluded point to be one that is imaged in the first frame but not …
evidences. We consider an occluded point to be one that is imaged in the first frame but not …
R2d2: Reliable and repeatable detector and descriptor
J Revaud, C De Souza… - Advances in neural …, 2019 - proceedings.neurips.cc
Interest point detection and local feature description are fundamental steps in many
computer vision applications. Classical approaches are based on a detect-then-describe …
computer vision applications. Classical approaches are based on a detect-then-describe …
Depth-aware video frame interpolation
Video frame interpolation aims to synthesize nonexistent frames in-between the original
frames. While significant advances have been made from the recent deep convolutional …
frames. While significant advances have been made from the recent deep convolutional …
Learning correspondence from the cycle-consistency of time
We introduce a self-supervised method for learning visual correspondence from unlabeled
video. The main idea is to use cycle-consistency in time as free supervisory signal for …
video. The main idea is to use cycle-consistency in time as free supervisory signal for …
Geonet: Unsupervised learning of dense depth, optical flow and camera pose
We propose GeoNet, a jointly unsupervised learning framework for monocular depth, optical
flow and ego-motion estimation from videos. The three components are coupled by the …
flow and ego-motion estimation from videos. The three components are coupled by the …