olivia23333 / e3gen Goto Github PK

When running the novel pose animation:
python demo/test_ani.py configs/ssdnerf_avatar_uncond_thuman_conv_16bit.py work_dirs/ssdnerf_avatar_uncond_16bit_thuman_conv/ckpt/ssdnerf_avatar_uncond_16bit_thuman_conv/latest.pth --gpu-ids 0
It report error:
~/E3Gen/lib/apis/test.py", line 238, in animate_3d data['cond_poses'] = data['cond_poses'][:, 31:32] KeyError: 'cond_poses'

Thanks for your great work!

I followed the training guidance and trained the model on 2 GPUs for 160,000 iters. But the rendered evaluation results look quite noisy and different from your checkpoint.

Below are the evaluation results under the viz_uncond folder.

Thanks for your work. But I have a question while reading the training part of the paper. It said Specifically, we first add Gaussian noise 𝜖 ∼ N (0, 𝐼) into the given generative UV features plane 𝑥𝑖 via a noise schedule comprising differentiable functions 𝛼 (𝑡) and 𝜎(𝑡), obtaining a noisy feature plane 𝑥𝑖(𝑡) := 𝛼 (𝑡)𝑥𝑖 + 𝜎(𝑡)𝜖 at diffusion time step 𝑡. T, however, at first we don't have any given UV features (The paper said they should be trained with the denoising training process), so what should the Gaussian noise be added to?