E3Gen
Preview：
Introduce：
E3Gen is a new digital avatar generation method that generates high-fidelity avatars in real time, with detailed clothing folds, and supports full control of multiple viewing angles and full-body poses, as well as property transfer and local editing. It addresses the incompatibility of 3D Gauss with current generation processes by encoding 3D Gauss into a structured 2D UV space, and explores expressive animation of 3D Gauss in training involving multiple agents.
https://pic.chinaz.com/ai/2024/06/24061410411855073943.jpg
Stakeholders:
E3Gen’s target audience is digital content creators, game developers, virtual reality experience designers, and others who need efficient and expressive avatar generation technology to enrich their products or services.
Usage Scenario Examples:
- E3Gen is used in game character design to generate personalised avatars
- E3Gen is used in virtual reality experiences to customize realistic avatars for users
- Use E3Gen to quickly generate art-inspired avatars in digital art creation
The features of the tool:
- The single-stage diffusion model trains both the denoising and fitting processes
- UV feature plane coding, realize 3D Gauss to 2D UV space conversion
- Part of the perception deformation module, to achieve the precise control of the whole body posture
- Support complex appearance and rich detail digital avatar generation
- Animation results for challenging new poses demonstrate strong robustness
- Support local editing and partial attribute transfer, editing results support posture control
Steps for Use:
- 1. Visit the E3Gen web link and learn about the products
- 2. Read the main function points of the product to understand its technical advantages
- 3. Select the corresponding function as required, such as posture control or local editing
- 4. Use E3Gen to generate digital avatars with specific properties
- 5. Edit the generated avatar to meet individual needs
- 6. Apply the edited avatar to the corresponding project or product
Tool’s Tabs: 3D avatar, digital generation
