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  library_name: keras
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  ## Model description
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- Full credits go to: [Vu Minh Chien](https://www.linkedin.com/in/vumichien/)
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- Depth estimation is a crucial step towards inferring scene geometry from 2D images. The goal in monocular depth estimation is to predict the depth value of each pixel or inferring depth information, given only a single RGB image as input.
 
 
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  ## Dataset
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  [NYU Depth Dataset V2](https://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html) is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect.
 
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  library_name: keras
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  ## Model description
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+ The original idea from Keras examples [Monocular depth estimation](https://keras.io/examples/vision/depth_estimation/) of [Victor Basu](https://www.linkedin.com/in/victor-basu-520958147/)
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+ Full credits go to [Vu Minh Chien](https://www.linkedin.com/in/vumichien/)
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+ Depth estimation is a crucial step towards inferring scene geometry from 2D images. The goal in monocular depth estimation is to predict the depth value of each pixel or infer depth information, given only a single RGB image as input.
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  ## Dataset
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  [NYU Depth Dataset V2](https://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html) is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect.