Abouee et al., 2024 - Google Patents
Weakly Supervised End2End Deep Visual OdometryAbouee et al., 2024
View PDF- Document ID
- 12637839151261421167
- Author
- Abouee A
- Ravi A
- Hinneburg L
- Dziwulski M
- Ölsner F
- Hess J
- Milz S
- Mäder P
- Publication year
- Publication venue
- Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
External Links
Snippet
Visual odometry is an ill-posed problem and utilized in many robotics applications especially automated driving for mapless navigation. Recent applications have shown that deep models outperform traditional approaches especially in localization accuracy and …
- 230000000007 visual effect 0 title abstract description 14
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30248—Vehicle exterior or interior
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
- G06T2207/10012—Stereo images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6288—Fusion techniques, i.e. combining data from various sources, e.g. sensor fusion
- G06K9/629—Fusion techniques, i.e. combining data from various sources, e.g. sensor fusion of extracted features
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Alkendi et al. | State of the art in vision-based localization techniques for autonomous navigation systems | |
| Fu et al. | PL-VINS: Real-time monocular visual-inertial SLAM with point and line features | |
| US10371529B2 (en) | Computational budget estimation for vision-aided inertial navigation systems | |
| Yin et al. | Scale recovery for monocular visual odometry using depth estimated with deep convolutional neural fields | |
| US9709404B2 (en) | Iterative Kalman Smoother for robust 3D localization for vision-aided inertial navigation | |
| Moreau et al. | Coordinet: uncertainty-aware pose regressor for reliable vehicle localization | |
| Krombach et al. | Combining feature-based and direct methods for semi-dense real-time stereo visual odometry | |
| Liu et al. | Direct visual odometry for a fisheye-stereo camera | |
| Zhao et al. | Good line cutting: Towards accurate pose tracking of line-assisted VO/VSLAM | |
| Rückert et al. | Snake-SLAM: Efficient global visual inertial SLAM using decoupled nonlinear optimization | |
| Zuo et al. | Cross-modal Semidense 6-DOF tracking of an event camera in challenging conditions | |
| Greene et al. | Metrically-scaled monocular slam using learned scale factors | |
| Françani et al. | Dense prediction transformer for scale estimation in monocular visual odometry | |
| Liu et al. | Real-time dense construction with deep multiview stereo using camera and imu sensors | |
| Yin et al. | Stereo visual odometry with automatic brightness adjustment and feature tracking prediction | |
| Pirvu et al. | Depth distillation: unsupervised metric depth estimation for UAVs by finding consensus between kinematics, optical flow and deep learning | |
| Mu et al. | Visual navigation features selection algorithm based on instance segmentation in dynamic environment | |
| Sun et al. | GGC-SLAM: A VSLAM system based on predicted static probability of feature points in dynamic environments | |
| Leng et al. | Cross-modal LiDAR-visual-inertial localization in prebuilt LiDAR point cloud map through direct projection | |
| Cao et al. | Eventboost: Event-based acceleration platform for real-time drone localization and tracking | |
| Wang et al. | Unsupervised scale network for monocular relative depth and visual odometry | |
| Abouee et al. | Weakly Supervised End2End Deep Visual Odometry | |
| Kuang et al. | A real-time and robust monocular visual inertial slam system based on point and line features for mobile robots of smart cities toward 6g | |
| Campos et al. | Scale-aware direct monocular odometry | |
| Liu et al. | A new dense hybrid stereo visual odometry approach |