U-Net: Going Deeper with Nested U-Structure for Salient Object Detection

📃 https://arxiv.org/abs/2005.09007v2

📦 https://github.com/NathanUA/U-2-Net

#segmentation #unet

Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation
* project page
* abs
* pdf
We present ObSuRF, a method which turns a single image of a scene into a 3D model represented as a set of NeRFs, with each NeRF corresponding to a different object. A single forward pass of an encoder network outputs a set of latent vectors describing the objects in the scene. These vectors are used independently to condition a NeRF decoder, defining the geometry and appearance of each object. We make learning more computationally efficient by deriving a novel loss, which allows training NeRFs on RGB-D inputs without explicit ray marching. We find that after training ObSuRF on RGB-D views of training scenes, it is capable of not only recovering the 3D geometry of a scene depicted in a single input image, but also to segment it into objects, despite receiving no supervision in that regard.
#nerf #segmentation #depth