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Monocular Depth Estimation

36 papers with code ยท Computer Vision
Subtask of Depth Estimation

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Latest papers without code

Progressive Fusion for Unsupervised Binocular Depth Estimation using Cycled Networks

17 Sep 2019

Extensive experiments on the publicly available datasets KITTI, Cityscapes and ApolloScape demonstrate the effectiveness of the proposed model which is competitive with other unsupervised deep learning methods for depth prediction.

DATA AUGMENTATION MONOCULAR DEPTH ESTIMATION STEREO DEPTH ESTIMATION

Task-Aware Monocular Depth Estimation for 3D Object Detection

17 Sep 2019

In this paper, we first analyse the data distributions and interaction of foreground and background, then propose the foreground-background separated monocular depth estimation (ForeSeE) method, to estimate the foreground depth and background depth using separate optimization objectives and depth decoders.

3D OBJECT DETECTION 3D OBJECT RECOGNITION MONOCULAR DEPTH ESTIMATION

Structure-Attentioned Memory Network for Monocular Depth Estimation

10 Sep 2019

To this end, we introduce a new Structure-Oriented Memory (SOM) module to learn and memorize the structure-specific information between RGB image domain and the depth domain.

DOMAIN ADAPTATION MONOCULAR DEPTH ESTIMATION

n-MeRCI: A new Metric to Evaluate the Correlation Between Predictive Uncertainty and True Error

20 Aug 2019

As deep learning applications are becoming more and more pervasive in robotics, the question of evaluating the reliability of inferences becomes a central question in the robotics community.

MONOCULAR DEPTH ESTIMATION

To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation

15 Aug 2019

Robust three-dimensional scene understanding is now an ever-growing area of research highly relevant in many real-world applications such as autonomous driving and robotic navigation.

AUTONOMOUS DRIVING DEPTH COMPLETION MONOCULAR DEPTH ESTIMATION MULTI-TASK LEARNING SCENE UNDERSTANDING

Structured Coupled Generative Adversarial Networks for Unsupervised Monocular Depth Estimation

15 Aug 2019

Inspired by the success of adversarial learning, we propose a new end-to-end unsupervised deep learning framework for monocular depth estimation consisting of two Generative Adversarial Networks (GAN), deeply coupled with a structured Conditional Random Field (CRF) model.

MONOCULAR DEPTH ESTIMATION

Index Network

11 Aug 2019

By viewing the indices as a function of the feature map, we introduce the concept of "learning to index", and present a novel index-guided encoder-decoder framework where indices are self-learned adaptively from data and are used to guide the downsampling and upsampling stages, without extra training supervision.

IMAGE DENOISING IMAGE MATTING MONOCULAR DEPTH ESTIMATION SEMANTIC SEGMENTATION

Enhancing self-supervised monocular depth estimation with traditional visual odometry

8 Aug 2019

Estimating depth from a single image represents an attractive alternative to more traditional approaches leveraging multiple cameras.

DEPTH AND CAMERA MOTION MONOCULAR DEPTH ESTIMATION VISUAL ODOMETRY

Semi-Supervised Adversarial Monocular Depth Estimation

6 Aug 2019

In this paper, we address the problem of monocular depth estimation when only a limited number of training image-depth pairs are available.

MONOCULAR DEPTH ESTIMATION

Adversarial View-Consistent Learning for Monocular Depth Estimation

4 Aug 2019

To this end, we first design a differentiable depth map warping operation, which is end-to-end trainable, and then propose a pose generator to generate novel views for a given image in an adversarial manner.

MONOCULAR DEPTH ESTIMATION