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 (14)

EVP: Enhanced Visual Perception Using Inverse Multi-attentive Feature Refinement And Regularized Image-text Alignment2023 · 7 citesNvs-monodepth: Improving Monocular Depth Prediction With Novel View Synthesis2021 · 10 citesIn Pixels We Trust: From Pixel Labeling To Object Localization And Scene Categorization2018 · 9 citesEnhancing Transformer-based Vision Models: Addressing Feature Map Anomalies Through Novel Optimization Strategies2025 · 3 citesRBF Weighted Hyper-Involution for RGB-D Object Detection2023 · 1 citesFutureDepth: Learning to Predict the Future Improves Video Depth Estimation2024 · 5 citesLightweight Prompt-guided CLIP Adaptation For Monocular Depth Estimation2026Attend Refine Repeat: Active Box Proposal Generation Via In-out Localization2016 · 18 citesSharpnet: Fast And Accurate Recovery Of Occluding Contours In Monocular Depth Estimation2019 · 10 citesImproving Task-specific Representation Via 1M Unlabelled Images Without Any Extra Knowledge2020 · 1 citesAutotaskformer: Searching Vision Transformers For Multi-task Learning2023Neural Radiance Field Codebooks2023Single image depth estimation by dilated deep residual convolutional neural network and soft-weight-sum inference2017 · 19 citesJoint Semantic Segmentation and Depth Estimation with Deep Convolutional Networks2016