# 3D Avatar

URAvatar is a novel avatar generation technology that enables the creation of realistic, re-lightable head avatars through smartphone scans under unknown lighting conditions. Unlike traditional methods that estimate reflectance parameters through inverse rendering, URAvatar directly simulates learned radiative transfer, effectively integrating global illumination into real-time rendering. This technology is significant as it can reconstruct head models that appear realistic in multiple environments from a single environmental smartphone scan, enabling real-time driving and re-lighting.

GAGAvatar is a Gaussian model-based technology for 3D avatar reconstruction and animation generation. It quickly generates 3D avatars from a single image and supports real-time facial expression animation. The main advantages of this technology include high-fidelity 3D model generation, fast rendering speed, and the ability to generalize to unseen identities. GAGAvatar captures identity and facial details through an innovative dual-improvement method and utilizes global image features and 3D deformable models to control expressions, providing a new benchmark for research and applications in digital avatars.

RodinHD is a high-fidelity 3D avatar generation technology based on diffusion models, developed by researchers including Bowen Zhang and Yiji Cheng. It aims to generate detailed 3D avatars from a single portrait image. This technology addresses the shortcomings of existing methods in capturing complex details such as hairstyles by employing novel data scheduling strategies and weight integration regularization terms, improving the decoder's ability to render sharp details. Additionally, it optimizes the guiding effect of portrait images through multi-scale feature representation and cross-attention mechanisms, resulting in 3D avatars with significantly enhanced detail compared to previous methods. Notably, it also exhibits strong generalization capabilities to wild portrait inputs.

E3Gen is a novel digital avatar generation method that can generate high-fidelity avatars in real time. It features detailed clothing wrinkles and supports comprehensive control over multiple perspectives and full-body poses, as well as attribute transfer and local editing. By encoding 3D Gaussian into a structured 2D UV space, E3Gen addresses the incompatibility issue between 3D Gaussian and current generation processes and explores the expressive animation of 3D Gaussian in training involving multiple subjects.

UltrAvatar is a realistic and movable 3D avatar generation model designed to bridge the gap between virtual and real-world experiences. It utilizes Score Distillation Sampling (SDS) loss, a differentiable renderer, and text conditioning to guide the diffusion model in generating 3D avatars. Compared to existing works, UltrAvatar presents a novel approach to 3D avatar generation by enhancing geometric fidelity and offering superior physical rendering texture quality. It employs a diffusion color extraction model and a realism-guided texture diffusion model to remove unnecessary lighting effects, presenting genuine diffusion colors, enabling the generated avatars to render realistically under various lighting conditions. Our experiments have proven the effectiveness and robustness of this method, significantly outperforming existing state-of-the-art approaches.

Shader is an AR beauty and special effect app. It offers a variety of real-time filters that can help users personalize their appearance and achieve virtual looks. Main functions include: real-time filters, makeup, body shaping, and 3D special effects. The product's advantage lies in its excellent filter effects and simple, user-friendly operation. Suitable for users who enjoy photo beautification.