深度学习入门(6) - 3DV 三维视觉

3DV

Two focus : predicting 3d shapes from image and processing 3d input data

Representations of 3D shape

Depth map

gives distance from the camera to the object in the world at that pixel

RGB image + Depth image = RGB-D Image (2.5D)

We can use Fully Convolutional network to predict the depth

problem : Scale / Depth Ambiguity

-> Use Scale invariant loss

Surface Normals

give a vector giving normal vector to the object in the world for that pixel

We can use Fully Convolutional network to predict Surface Normals

loss: $\frac{xy}{|x||y|}$

Also can’t represent the occluded objects

Voxel Grid

Represent a shape with a $V\times V\times V$ grid of occupancies (just like minecraft 😃

Problems: Need high