Depth Estimation
Leaderboards
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
|---|---|---|---|---|---|---|
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Subtasks
Greatest papers with code
Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics
We present an approach which takes advantage of both structure and semantics for unsupervised monocular learning of depth and ego-motion.
Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos
Models and examples built with TensorFlow
#15 best model for
Monocular Depth Estimation
on KITTI Eigen split
Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints
CVPR 2018
• tensorflow/models
• 
We present a novel approach for unsupervised learning of depth and ego-motion from monocular video.
Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras
ICCV 2019
• google-research/google-research
•
We present a novel method for simultaneous learning of depth, egomotion, object motion, and camera intrinsics from monocular videos, using only consistency across neighboring video frames as supervision signal.
Unsupervised Monocular Depth Estimation with Left-Right Consistency
CVPR 2017
• mrharicot/monodepth
•
Learning based methods have shown very promising results for the task of depth estimation in single images.
#9 best model for
Monocular Depth Estimation
on KITTI Eigen split
Unsupervised Learning of Depth and Ego-Motion from Video
CVPR 2017
• tinghuiz/SfMLearner
•
We present an unsupervised learning framework for the task of monocular depth and camera motion estimation from unstructured video sequences.
Digging Into Self-Supervised Monocular Depth Estimation
ICCV 2019
• nianticlabs/monodepth2
• 
Per-pixel ground-truth depth data is challenging to acquire at scale.
Digging Into Self-Supervised Monocular Depth Estimation
Per-pixel ground-truth depth data is challenging to acquire at scale.
#7 best model for
Monocular Depth Estimation
on KITTI Eigen split
Deeper Depth Prediction with Fully Convolutional Residual Networks
• iro-cp/FCRN-DepthPrediction
•
This paper addresses the problem of estimating the depth map of a scene given a single RGB image.
3D Ken Burns Effect from a Single Image
According to this depth estimate, our framework then maps the input image to a point cloud and synthesizes the resulting video frames by rendering the point cloud from the corresponding camera positions.
SOTA for Depth Estimation on NYU-Depth V2