AvatarCLIP
giraffe
| AvatarCLIP | giraffe | |
|---|---|---|
| 4 | 3 | |
| 1,040 | 1,229 | |
| - | 0.5% | |
| 0.0 | 1.8 | |
| about 1 year ago | over 2 years ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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AvatarCLIP
- Half way in my AA college career and just started my electives. Need help
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[R] Text to 3D characters + expression editing + pose generation
Based on similar works CLIPActor and AvatarCLIP the codebase implements similar pipeline using mesh and differentiable rasterization to provide a spedeup allowing for ~10 min character generation on a weak Google Colab GPU
- "AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars", Hong et al 2022 (crosspost of another user's post)
- "AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars", Hong et al 2022
giraffe
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[D] CVPR 2021 Best Paper (GIRAFFE) explained: Representing Scenes as Compositional Generative Neural Feature Fields by Michael Niemeyer et al.
[Full Explanation Post] [Arxiv] [Code]
- CVPR 2021 Best Paper Award: GIRAFFE - Controllable Image Generation - How to train the network from scratch with a custom Dataset?
- CVPR 2021 Best Paper Award: GIRAFFE - Controllable Image Generation
What are some alternatives?
CIPS-3D - 3D-aware GANs based on NeRF (arXiv).
PET-NeuS - PET-NeuS: Positional Encoding Tri-Planes for Neural Surfaces (CVPR 2023)
multinerf - A Code Release for Mip-NeRF 360, Ref-NeRF, and RawNeRF
ALAE - [CVPR2020] Adversarial Latent Autoencoders
Make-It-3D - [ICCV 2023] Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior
pi-GAN-pytorch - Implementation of π-GAN, for 3d-aware image synthesis, in Pytorch
MotionDiffuse - MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model
SDV - Synthetic data generation for tabular data
stable-dreamfusion - Text-to-3D & Image-to-3D & Mesh Exportation with NeRF + Diffusion.
stylegan2-pytorch - Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
Papers-in-100-Lines-of-Code - Implementation of papers in 100 lines of code.