Jianchun Chen jianchuc@andrw.cmu.edu
To reproduce the result, please run
CUDA_VISIBLE_DEVICES={your gpu id} python main.py



It contains 4 vertices and 4 triangular faces.

It contains 8 vertices and 12 triangular faces from 6 rectangular faces.

The two colors are chosed as red [1,0,0] and green [0,1,0].
R = [[0,-1,0],[1,0,0],[0,0,1]], t=[0,0,0]

R = [[1,0,0],[0,1,0],[0,0,1]], t=[0,0,1]

R = [[1,0,0],[0,1,0],[0,0,1]], t=[0.5,-0.5,0]

R = [[0,0,1],[0,1,0],[-1,0,0]], t=[3,0,3]

The rendered point clouds from the first, second images and the union are shown respectively.





The time and memory comparison between parametric function with 200*200 points and implicit surface with 64*64*3 voxel are shown in the table below.
| \ | Parametric Functions | Implicit Surface |
|---|---|---|
| Time (s) | 2.64 | 4.49 |
| Memory (MB) | 1409 | 1477 |
Generally, the parametric function is easier to use with faster speed and lower memory use. The quality depends on the resolution of the grid/voxel we use. However, the advantage of implicit surface is that it is a dense representation of a 3D structure.
To reproduce the result, please prepare a sequence of human model from CAPE dataset and two UV texture map. The texture map I used here is generated by Re-Identification Supervised Texture Generation.
The gif below shows a dynamic human gradually changing its cloth texture.

The sampled point clouds from the cow mesh with 10,100,1000,10000 points are shown below respectively.



