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Train high dimensional features #15
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If high_dim_feature has a shape of [P, N, C], it should work. The feature maps will be obtained through alpha blending. |
Can you elaborate more on what P, N, C represent respectively? I originally thought the shape should be like [N, C] where N is the number of Gaussian and C is the channel number |
Hmm, I've made an mistake. The correct notation is [P, C], where P represents the point number and C denotes the channel. You're absolutely right. |
Would you be so kind as to provide some data for this? |
Hi! If I want to train and render an additional high-dimensional feature vector for each Gaussian, should I revise the following part in gaussian_render? Besides this part, what else should I do?
I tried to render an already-trained Gaussian model with high-dim features, but the rendered features were not as expected.
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