Papers Stereo Matching Hand
“Stereo Matching Hand” 태그가 달린 논문 163편 · 필터 해제
Object-Centric Stereo Matching for 3D Object Detection
Safe autonomous driving requires reliable 3D object detection-determining the 6 DoF pose and dimensions of objects of interest. Using stereo cameras to solve this task is a cost-effective alternative to the widely used L…
3D Object Detection3D Object Detection From Stereo ImagesAutonomous DrivingDisparity Estimation+5Real-Time Variational Fisheye Stereo without Rectification and Undistortion
Dense 3D maps from wide-angle cameras is beneficial to robotics applications such as navigation and autonomous driving. In this work, we propose a real-time dense 3D mapping method for fisheye cameras without explicit re…
Autonomous DrivingStereo MatchingStereo Matching HandLearning Residual Flow as Dynamic Motion from Stereo Videos
We present a method for decomposing the 3D scene flow observed from a moving stereo rig into stationary scene elements and dynamic object motion. Our unsupervised learning framework jointly reasons about the camera motio…
Depth And Camera MotionMotion EstimationOptical Flow EstimationStereo Matching+2DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch
Our goal is to significantly speed up the runtime of current state-of-the-art stereo algorithms to enable real-time inference. Towards this goal, we developed a differentiable PatchMatch module that allows us to discard …
Stereo MatchingStereo Matching HandAdaptive Unimodal Cost Volume Filtering for Deep Stereo Matching
State-of-the-art deep learning based stereo matching approaches treat disparity estimation as a regression problem, where loss function is directly defined on true disparities and their estimated ones. However, disparity…
Disparity EstimationregressionStereo MatchingStereo Matching HandRobust Full-FoV Depth Estimation in Tele-wide Camera System
Tele-wide camera system with different Field of View (FoV) lenses becomes very popular in recent mobile devices. Usually it is difficult to obtain full-FoV depth based on traditional stereo-matching methods. Pure Deep Ne…
DecoderDepth EstimationDepth PredictionStereo Matching+1Multi-Spectral Visual Odometry without Explicit Stereo Matching
Multi-spectral sensors consisting of a standard (visible-light) camera and a long-wave infrared camera can simultaneously provide both visible and thermal images. Since thermal images are independent from environmental i…
3D ReconstructionStereo MatchingStereo Matching HandVisual OdometryOmniMVS: End-to-End Learning for Omnidirectional Stereo Matching
In this paper, we propose a novel end-to-end deep neural network model for omnidirectional depth estimation from a wide-baseline multi-view stereo setup. The images captured with ultra wide field-of-view (FOV) cameras on…
DecoderDepth EstimationStereo MatchingStereo Matching HandStereo Event Lifetime and Disparity Estimation for Dynamic Vision Sensors
Event-based cameras are biologically inspired sensors that output asynchronous pixel-wise brightness changes in the scene called events. They have a high dynamic range and temporal resolution of a microsecond, opposed to…
Disparity EstimationStereo MatchingStereo Matching HandEnd-to-End Learning of Multi-scale Convolutional Neural Network for Stereo Matching
Deep neural networks have shown excellent performance in stereo matching task. Recently CNN-based methods have shown that stereo matching can be formulated as a supervised learning task. However, less attention is paid o…
Disparity EstimationStereo MatchingStereo Matching HandAppearance and Shape from Water Reflection
This paper introduces single-image geometric and appearance reconstruction from water reflection photography, i.e., images capturing direct and water-reflected real-world scenes. Water reflection offers an additional vie…
3D Scene ReconstructionStereo MatchingStereo Matching HandTW-SMNet: Deep Multitask Learning of Tele-Wide Stereo Matching
In this paper, we introduce the problem of estimating the real world depth of elements in a scene captured by two cameras with different field of views, where the first field of view (FOV) is a Wide FOV (WFOV) captured b…
Depth EstimationDisparity EstimationStereo MatchingStereo Matching HandDrivingStereo: A Large-Scale Dataset for Stereo Matching in Autonomous Driving Scenarios
Great progress has been made on estimating disparity maps from stereo images. However, with the limited stereo data available in the existing datasets and unstable ranging precision of current stereo methods, industry-le…
Autonomous DrivingStereo MatchingStereo Matching HandSDC - Stacked Dilated Convolution: A Unified Descriptor Network for Dense Matching Tasks
Dense pixel matching is important for many computer vision tasks such as disparity and flow estimation. We present a robust, unified descriptor network that considers a large context region with high spatial variance. O…
Optical Flow EstimationStereo MatchingStereo Matching HandMulti-Level Context Ultra-Aggregation for Stereo Matching
Exploiting multi-level context information to cost volume can improve the performance of learning-based stereo matching methods. In recent years, 3-D Convolution Neural Networks (3-D CNNs) show the advantages in regulari…
Stereo MatchingStereo Matching HandLocal Detection of Stereo Occlusion Boundaries
Stereo occlusion boundaries are one-dimensional structures in the visual field that separate foreground regions of a scene that are visible to both eyes (binocular regions) from background regions of a scene that are vis…
Stereo MatchingStereo Matching HandDISCO: Depth Inference from Stereo using Context
Recent deep learning based approaches have outperformed classical stereo matching methods. However, current deep learning based end-to-end stereo matching methods adopt a generic encoder-decoder style network with skip c…
DecoderStereo MatchingStereo Matching HandExtending Monocular Visual Odometry to Stereo Camera Systems by Scale Optimization
This paper proposes a novel approach for extending monocular visual odometry to a stereo camera system. The proposed method uses an additional camera to accurately estimate and optimize the scale of the monocular visual …
Monocular Visual OdometryStereo MatchingStereo Matching HandVisual OdometryGuided Stereo Matching
Stereo is a prominent technique to infer dense depth maps from images, and deep learning further pushed forward the state-of-the-art, making end-to-end architectures unrivaled when enough data is available for training. …
Stereo MatchingStereo Matching HandBridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence
Stereo matching and flow estimation are two essential tasks for scene understanding, spatially in 3D and temporally in motion. Existing approaches have been focused on the unsupervised setting due to the limited resource…
Optical Flow EstimationScene UnderstandingStereo MatchingStereo Matching Hand