[CVPR 2022] "MonoScene: Monocular 3D Semantic Scene Completion": 3D Semantic Occupancy Prediction from a single image

[CVPR 2021] Monocular depth estimation using wavelets for efficiency

ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentation (ICCV 2021)

Monocular Depth Estimation Toolbox and Benchmark. [Arxiv'24 ScaleDepth, TCSVT'24 Plane2Depth, TIP'24 Binsformer]

Python toolbox for the NYU Depth Dataset V2

[ECCV 2024] Monocular Occupancy Prediction for Scalable Indoor Scenes

Monocular depth prediction with PyTorch

Depth estimation from RGB images using fully convolutional neural networks.

[SAIN'18] [Caffe] A dilated version of FCN with Stride 2 for Efficient Semantic Segmentation

Depth estimation from RGB images using a DenseNet based deep model.

Practical Depth Estimation with Image Segmentation and Serial U-Nets

PyTorch Implementation of "NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction"

A PyTorch implementation of "Revisiting Multi-Task Learning with ROCK: a Deep Residual Auxiliary Block for Visual Detection"

Object detection method that can simultaneously estimate the positions and depth of the objects from images

Simple Tool To Extract nyu_depth_v2_labeled.mat

This is the code for the work "Single image dehazing using improved cycleGAN" published in the Journal of Visual Communication and Image Representation.

Towards Online Waypoint Generation for a Quadrotor Using Enhanced Monocular Depth Estimation.

Replicated results from DenseDepth using DenseNet169 in Python.

Single Image Depth Estimation using UNet architecture trained on NYU Depth V2 dataset. Predicts depth maps from RGB images using PyTorch.

Towards Online Waypoint Generation for a Quadrotor Using Enhanced Monocular Depth Estimation.