Stereo Depth Estimation Edit Task
Computer Vision • Depth Estimation
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Benchmarks
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
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Greatest papers with code
Efficient Attention: Attention with Linear Complexities
• lucidrains/stylegan2-pytorch
• 
Dot-product attention has wide applications in computer vision and natural language processing.
IMAGE CLASSIFICATION INSTANCE SEGMENTATION OBJECT DETECTION OBJECT RECOGNITION SEMANTIC SEGMENTATION STEREO DEPTH ESTIMATION
On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach
Despite the progress on monocular depth estimation in recent years, we show that the gap between monocular and stereo depth accuracy remains large$-$a particularly relevant result due to the prevalent reliance upon monocular cameras by vehicles that are expected to be self-driving.
Why Having 10,000 Parameters in Your Camera Model Is Better Than Twelve
In contrast, generic camera models allow for very accurate calibration due to their flexibility.
Why Having 10,000 Parameters in Your Camera Model is Better Than Twelve
In contrast, generic camera models allow for very accurate calibration due to their flexibility.
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
ICLR 2020
• mileyan/Pseudo_Lidar_V2
•
In this paper we provide substantial advances to the pseudo-LiDAR framework through improvements in stereo depth estimation.
3D OBJECT DETECTION AUTONOMOUS DRIVING STEREO DEPTH ESTIMATION
Anytime Stereo Image Depth Estimation on Mobile Devices
• mileyan/AnyNet
•
Many applications of stereo depth estimation in robotics require the generation of accurate disparity maps in real time under significant computational constraints.
Ranked #1 on
Stereo Depth Estimation
on KITTI2015
Real-time self-adaptive deep stereo
CVPR 2019
• CVLAB-Unibo/Real-time-self-adaptive-deep-stereo
• 
Deep convolutional neural networks trained end-to-end are the state-of-the-art methods to regress dense disparity maps from stereo pairs.
Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers
• mli0603/stereo-transformer
•
Stereo depth estimation relies on optimal correspondence matching between pixels on epipolar lines in the left and right images to infer depth.
Bi3D: Stereo Depth Estimation via Binary Classifications
CVPR 2020
• NVlabs/Bi3D
•
Given a strict time budget, Bi3D can detect objects closer than a given distance in as little as a few milliseconds, or estimate depth with arbitrarily coarse quantization, with complexity linear with the number of quantization levels.
UnOS: Unified Unsupervised Optical-Flow and Stereo-Depth Estimation by Watching Videos
CVPR 2019
• baidu-research/UnDepthflow
•
In this paper, we propose UnOS, an unified system for unsupervised optical flow and stereo depth estimation using convolutional neural network (CNN) by taking advantages of their inherent geometrical consistency based on the rigid-scene assumption.
4 MOTION SEGMENTATION OPTICAL FLOW ESTIMATION STEREO DEPTH ESTIMATION VISUAL ODOMETRY