[CVPR 2022] "MonoScene: Monocular 3D Semantic Scene Completion": 3D Semantic Occupancy Prediction from a single image
-
Updated
Apr 6, 2024 - Python
[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
[ICLR 2024] DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation
ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentation (ICCV 2021)
Monocular Depth Estimation Toolbox and Benchmark.
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
[ECCV 2024] Monocular Occupancy Prediction for Scalable Indoor Scenes
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"
Simple Tool To Extract nyu_depth_v2_labeled.mat
Object detection method that can simultaneously estimate the positions and depth of the objects from images
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.
Towards Online Waypoint Generation for a Quadrotor Using Enhanced Monocular Depth Estimation.
Towards Online Waypoint Generation for a Quadrotor Using Enhanced Monocular Depth Estimation.
Add a description, image, and links to the nyu-depth-v2 topic page so that developers can more easily learn about it.
To associate your repository with the nyu-depth-v2 topic, visit your repo's landing page and select "manage topics."