Stereo Depth Estimation
46 papers with code • 5 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Stereo Depth Estimation
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Libraries
Use these libraries to find Stereo Depth Estimation models and implementationsDatasets
KITTI
Spring
GUISS dataset
Latest papers with no code
FoVA-Depth: Field-of-View Agnostic Depth Estimation for Cross-Dataset Generalization
Unfortunately, most of the GT data is for pinhole cameras, making it impossible to properly train depth estimation models for large-FoV cameras.
ARAI-MVSNet: A multi-view stereo depth estimation network with adaptive depth range and depth interval
Moreover, our method also achieves the lowest $e_{1}$ and $e_{3}$ on the BlendedMVS dataset and the highest Acc and $F_{1}$-score on the ETH 3D dataset, surpassing all listed methods. Project website: https://github. com/zs670980918/ARAI-MVSNet
FusionDepth: Complement Self-Supervised Monocular Depth Estimation with Cost Volume
Multi-view stereo depth estimation based on cost volume usually works better than self-supervised monocular depth estimation except for moving objects and low-textured surfaces.
DPS-Net: Deep Polarimetric Stereo Depth Estimation
Stereo depth estimation usually struggles to deal with textureless scenes for both traditional and learning-based methods due to the inherent dependence on image correspondence matching.
Depth Estimation maps of lidar and stereo images
The structure of this paper is made of by following:(1) Performance: to discuss and evaluate about depth maps created from stereo images and 3D cloud points, and relationships analysis for alignment and errors;(2) Depth estimation by stereo images: to explain the methods about how to use stereo images to estimate depth;(3)Depth estimation by lidar: to explain the methods about how to use 3d cloud datas to estimate depth;In summary, this report is mainly to show the performance of depth maps and their approaches, analysis for them.
A Practical Stereo Depth System for Smart Glasses
We present the design of a productionized end-to-end stereo depth sensing system that does pre-processing, online stereo rectification, and stereo depth estimation with a fallback to monocular depth estimation when rectification is unreliable.
2T-UNET: A Two-Tower UNet with Depth Clues for Robust Stereo Depth Estimation
Additionally, the input for twin encoders in 2T-UNet are different compared to the existing stereo methods.
Uncertainty Guided Depth Fusion for Spike Camera
In this paper, we propose a novel Uncertainty-Guided Depth Fusion (UGDF) framework to fuse the predictions of monocular and stereo depth estimation networks for spike camera.
Accurate and Real-time Pseudo Lidar Detection: Is Stereo Neural Network Really Necessary?
In the experiments, we develop a system with a less powerful stereo matching predictor and adopt the proposed refinement schemes to improve the accuracy.
MEStereo-Du2CNN: A Novel Dual Channel CNN for Learning Robust Depth Estimates from Multi-exposure Stereo Images for HDR 3D Applications
Secondly, we combine disparity maps obtained from the stereo images at different exposure levels using a robust disparity feature fusion approach.
