336 skills found · Page 1 of 12
raulmur / ORB SLAM2Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities
luigifreda / PyslampySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.
HuajianUP / Photo SLAM[CVPR 2024] Photo-SLAM: Real-time Simultaneous Localization and Photorealistic Mapping for Monocular, Stereo, and RGB-D Cameras
erget / StereoVisionLibrary and utilities for 3d reconstruction from stereo cameras.
sourishg / Stereo Calibration:camera: :camera: Stereo camera calibration using OpenCV and C++
fabiotosi92 / Awesome Deep Stereo MatchingA curated list of awesome Deep Stereo Matching resources
PeterFWS / Structure PLP SLAM[ICRA'23] The official Implementation of "Structure PLP-SLAM: Efficient Sparse Mapping and Localization using Point, Line and Plane for Monocular, RGB-D and Stereo Cameras"
RonaldSun / VI Stereo DSODirect sparse odometry combined with stereo cameras and IMU
LearnTechWithUs / Stereo VisionThis program has been developed as part of a project at the University of Karlsruhe in Germany. The final purpose of the algorithm is to measure the distance to an object by combining two webcams and use them as a Stereo Camera.
megvii-research / OccDepthMaybe the first academic open work on stereo 3D SSC method with vision-only input.
TemugeB / Python Stereo Camera CalibrateStereo camera calibration with python and openCV
yiakwy / SEMANTIC VISUAL SUPPORTED ODEMETRYsemantic visual slam for monocular and stereo camera devices
HKUST-Aerial-Robotics / GVINS DatasetA dataset containing synchronized visual, inertial and GNSS raw measurements.
DSaurus / DiffuStereoThis repository is the official implementation of DiffuStereo: High Quality Human Reconstruction via Diffusion-based Stereo Using Sparse Cameras.
USTCPCS / CVPR2018 AttentionContext Encoding for Semantic Segmentation MegaDepth: Learning Single-View Depth Prediction from Internet Photos LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume On the Robustness of Semantic Segmentation Models to Adversarial Attacks SPLATNet: Sparse Lattice Networks for Point Cloud Processing Left-Right Comparative Recurrent Model for Stereo Matching Enhancing the Spatial Resolution of Stereo Images using a Parallax Prior Unsupervised CCA Discovering Point Lights with Intensity Distance Fields CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation Learning a Discriminative Feature Network for Semantic Segmentation Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi- Supervised Semantic Segmentation Unsupervised Deep Generative Adversarial Hashing Network Monocular Relative Depth Perception with Web Stereo Data Supervision Single Image Reflection Separation with Perceptual Losses Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains EPINET: A Fully-Convolutional Neural Network for Light Field Depth Estimation by Using Epipolar Geometry FoldingNet: Interpretable Unsupervised Learning on 3D Point Clouds Decorrelated Batch Normalization Unsupervised Learning of Depth and Egomotion from Monocular Video Using 3D Geometric Constraints PU-Net: Point Cloud Upsampling Network Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer Tell Me Where To Look: Guided Attention Inference Network Residual Dense Network for Image Super-Resolution Reflection Removal for Large-Scale 3D Point Clouds PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image Fully Convolutional Adaptation Networks for Semantic Segmentation CRRN: Multi-Scale Guided Concurrent Reflection Removal Network DenseASPP: Densely Connected Networks for Semantic Segmentation SGAN: An Alternative Training of Generative Adversarial Networks Multi-Agent Diverse Generative Adversarial Networks Robust Depth Estimation from Auto Bracketed Images AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation DeepMVS: Learning Multi-View Stereopsis GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation Single-Image Depth Estimation Based on Fourier Domain Analysis Single View Stereo Matching Pyramid Stereo Matching Network A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation Image Correction via Deep Reciprocating HDR Transformation Occlusion Aware Unsupervised Learning of Optical Flow PAD-Net: Multi-Tasks Guided Prediciton-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing Surface Networks Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation TextureGAN: Controlling Deep Image Synthesis with Texture Patches Aperture Supervision for Monocular Depth Estimation Two-Stream Convolutional Networks for Dynamic Texture Synthesis Unsupervised Learning of Single View Depth Estimation and Visual Odometry with Deep Feature Reconstruction Left/Right Asymmetric Layer Skippable Networks Learning to See in the Dark
sourishg / Fisheye Stereo Calibration:camera: :camera: Fisheye stereo calibration using OpenCV and C++
astar-ai / CalicamCaliCam: Calibrated Fisheye Stereo & Mono Camera
bvnayak / Stereo CalibrationStereo Camera Calibration using Python-OpenCV
NVIDIA / 3DObjectReconstruction3D Object Reconstruction project is a workflow that takes a set of stereo images and camera info and outputs a textured mesh (i.e., .OBJ file). The purpose is to translate physical items into the digital world in a photorealistic way
NVIDIA-ISAAC-ROS / Isaac Ros Dnn Stereo DepthNVIDIA-accelerated, deep learned stereo disparity estimation
