Stereo Depth Estimation

43 papers with code • 5 benchmarks • 3 datasets

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Use these libraries to find Stereo Depth Estimation models and implementations

Most implemented papers

Efficient Attention: Attention with Linear Complexities

cmsflash/efficient-attention 4 Dec 2018

Dot-product attention has wide applications in computer vision and natural language processing.

HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching

google-research/google-research CVPR 2021

Contrary to many recent neural network approaches that operate on a full cost volume and rely on 3D convolutions, our approach does not explicitly build a volume and instead relies on a fast multi-resolution initialization step, differentiable 2D geometric propagation and warping mechanisms to infer disparity hypotheses.

Pyramid Stereo Matching Network

JiaRenChang/PSMNet CVPR 2018

The spatial pyramid pooling module takes advantage of the capacity of global context information by aggregating context in different scales and locations to form a cost volume.

On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach

NVIDIA-Jetson/redtail 26 Mar 2018

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.

GA-Net: Guided Aggregation Net for End-to-end Stereo Matching

feihuzhang/GANet CVPR 2019

In the stereo matching task, matching cost aggregation is crucial in both traditional methods and deep neural network models in order to accurately estimate disparities.

MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching

cogsys-tuebingen/mobilestereonet 22 Aug 2021

Depending on the dimension of cost volume, we design a 2D and a 3D model with encoder-decoders built from 2D and 3D convolutions, respectively.

StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction

meteorshowers/StereoNet ECCV 2018

A first estimate of the disparity is computed in a very low resolution cost volume, then hierarchically the model re-introduces high-frequency details through a learned upsampling function that uses compact pixel-to-pixel refinement networks.

Anytime Stereo Image Depth Estimation on Mobile Devices

mileyan/AnyNet 26 Oct 2018

Many applications of stereo depth estimation in robotics require the generation of accurate disparity maps in real time under significant computational constraints.

Nighttime Stereo Depth Estimation using Joint Translation-Stereo Learning: Light Effects and Uninformative Regions

aasharma90/NighttimeDepthandFlow 30 Sep 2019

To address the problem, we introduce a network joining day/night translation and stereo.

Why Having 10,000 Parameters in Your Camera Model is Better Than Twelve

puzzlepaint/camera_calibration 5 Dec 2019

In contrast, generic camera models allow for very accurate calibration due to their flexibility.