NYU Depth V2

NYU Depth V2


NYU Depth V2


NYU Depth V2

Use Case

Computer Vision


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

NYU Depth V2

About Dataset

 It features:

  • 1449 densely labeled pairs of aligned RGB and depth images
  • 464 new scenes taken from 3 cities
  • 407,024 new unknown frames
  • Each object is labeled with a class and an instance number (cup1, cup2, cup3, etc)

The dataset has several components:

  • Labeled: A subset of the video data advised by dense multi-class labels.
  • Raw: The raw RGB, depth, and motion sensor data as provided by the Kinect.

Toolbox: Useful functions for shape the data and labels.

Applications and Use Cases

Depth Estimation Algorithms

The NYU Depth V2 dataset serves as a guage for training and evaluating depth estimation algorithms. Researchers leverage this rich repository of visual data to develop robust models capable of accurately predicting depth information from RGB images, thereby advancing the frontiers of computer vision.

Scene Understanding and Object Recognition

Beyond depth estimation, the dataset facilitates advancements in scene understanding and object recognition. By analyzing the spatial layout and semantic content of indoor scenes, researchers can develop sophisticated algorithms capable of identifying objects, parsing scenes, and understanding contextual relationships.

Implications for Research and Innovation

Autonomous Navigation Systems

The insights gleaned from the NYU Depth V2 dataset hold profound implications for autonomous navigation systems. By integrating depth perception capabilities, autonomous vehicles and robotic platforms can navigate complex indoor environments with unprecedented precision and safety.

Augmented Reality and Virtual Reality

By leveraging precise depth information, developers can create immersive AR/VR experiences that seamlessly integrate virtual elements with real-world environments, enhancing user engagement and interaction.

Ethical Considerations and Privacy Safeguards

Data Privacy and Security

As stewards of data, we recognize the importance of prioritizing data privacy and security. The NYU Depth V2 dataset is curated and maintained with utmost diligence to safeguard sensitive information and mitigate the risks of unauthorized access or misuse.

Ethical Data Usage

 We advocate for transparent communication, informed consent, and responsible data stewardship to uphold the rights and dignity of individuals represented in the dataset.


 As custodians of this invaluable resource, we remain committed to advancing scientific knowledge, fostering innovation, and upholding ethical standards in data utilization.

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