#
controllable-generation
Here are
34 public repositories
matching this topic...
Updated
Aug 29, 2023
Python
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Updated
Nov 25, 2022
Jupyter Notebook
Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Updated
Nov 29, 2022
Jupyter Notebook
PyTorch implementation for SDEdit: Image Synthesis and Editing with Stochastic Differential Equations
Updated
Feb 12, 2023
Python
A collection of resources on controllable generation with text-to-image diffusion models.
Official implementation of "DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents"
Updated
Sep 10, 2022
Python
Update-to-data resources for conditional content generation, including human motion generation, image or video generation and editing.
Official implementation of "Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting"
Updated
May 30, 2024
Python
[CVPR 2024] Official implementation of "Towards Realistic Scene Generation with LiDAR Diffusion Models"
Updated
May 21, 2024
Python
A curated list of resources of audio-driven talking face generation
Official PyTorch Implementation for InfoSwap
Updated
Feb 16, 2022
Python
[ICML 2023] Official PyTorch Implementation of "Hierarchical Neural Coding for Controllable CAD Model Generation".
Updated
May 6, 2024
Python
[Paperlist] Awesome paper list of controllable text generation via latent auto-encoders. Contributions of any kind are welcome.
[Preprint] AdaVAE: Exploring Adaptive GPT-2s in VAEs for Language Modeling PyTorch Implementation
Updated
Oct 18, 2023
Python
Updated
May 29, 2023
Jupyter Notebook
[KBS] PCAE: A Framework of Plug-in Conditional Auto-Encoder for Controllable Text Generation PyTorch Implementation
Updated
Apr 10, 2023
Python
Controllable mage captioning model with unsupervised modes
Updated
Apr 14, 2023
Python
Updated
Apr 30, 2024
Python
Code for "Data-to-text Generation with Style Imitation." [Findings of EMNLP 2020]
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