NYU Depth V2

The NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect.

Papers using NYU Depth V2 (13)

Single image depth estimation by dilated deep residual convolutional neural network and soft-weight-sum inference2017 · 19 citesAttend Refine Repeat: Active Box Proposal Generation Via In-out Localization2016 · 18 citesNvs-monodepth: Improving Monocular Depth Prediction With Novel View Synthesis2021 · 10 citesSharpnet: Fast And Accurate Recovery Of Occluding Contours In Monocular Depth Estimation2019 · 10 citesIn Pixels We Trust: From Pixel Labeling To Object Localization And Scene Categorization2018 · 9 citesEVP: Enhanced Visual Perception Using Inverse Multi-attentive Feature Refinement And Regularized Image-text Alignment2023 · 7 citesEnhancing Transformer-based Vision Models: Addressing Feature Map Anomalies Through Novel Optimization Strategies2025 · 3 citesRBF Weighted Hyper-Involution for RGB-D Object Detection2023 · 1 citesImproving Task-specific Representation Via 1M Unlabelled Images Without Any Extra Knowledge2020 · 1 citesJoint Semantic Segmentation and Depth Estimation with Deep Convolutional Networks2016Autotaskformer: Searching Vision Transformers For Multi-task Learning2023Lightweight Prompt-guided CLIP Adaptation For Monocular Depth Estimation2026Neural Radiance Field Codebooks2023