# High Fidelity

Animate Anyone 2 is a character image animation technology based on diffusion models that can generate animations highly adapted to the environment. It addresses the issue of insufficient correlation between characters and environments in traditional methods by extracting environmental representations as conditional inputs. The main advantages of this technology include high fidelity, strong environmental adaptability, and excellent dynamic motion handling capabilities. It is suitable for scenarios requiring high-quality animation generation, such as film production and game development, helping creators quickly produce character animations with environmental interaction, saving time and costs.

GaussianSpeech is an innovative method capable of synthesizing high-fidelity animated sequences from speech signals to create realistic, personalized 3D head avatars. The technology combines speech signals with 3D Gaussian drawing techniques to capture human head expressions and detailed movements, including skin wrinkling and finer facial motions. Key advantages of GaussianSpeech include real-time rendering speed, natural visual dynamics, and the ability to exhibit a variety of facial expressions and styles. The underlying technology involves the creation of large-scale, multi-view audio-visual sequence datasets and the development of audio conditional transformation models that can directly extract lip and expression features from audio input.

CHANGER is an innovative industrial-grade head blending technology that achieves high-fidelity head blending effects through chroma key technology, especially suitable for fields such as visual effects (VFX), digital character creation, and virtual avatars. This technology separates background integration from foreground blending, utilizes chroma key to generate a flawless background, and incorporates head shape and long hair enhancement (H^2 enhancement) along with the foreground predictive attention transformer (FPAT) module to improve its generalizability to diverse real-world scenarios. The main advantages of CHANGER include high fidelity, industrial-grade results, and extensive applicability to real-world cases.

This is an advanced video generation model based on the AsymmDiT architecture, available for free trial. It generates high-fidelity videos, bridging the gap between open-source and proprietary video generation systems. The model requires at least 4 H100 GPUs to run.

HelloMeme is a diffusion model that incorporates spatially woven attention, designed to embed high fidelity and rich conditions into the image generation process. This technology generates videos by extracting features from each frame of the driving video and using them as input to the HMControlModule. Further optimization through the Animatediff module improves the continuity and fidelity of the generated videos. Additionally, HelloMeme supports facial expression control through ARKit's blend shapes, and enables the seamless integration of SD1.5-based Lora or Checkpoint, ensuring that it does not compromise the generalization ability of the T2I model.

Stable-Hair is an innovative hairstyle transfer technique that robustly transfers a diverse range of real-world hairstyles onto user-provided facial images for virtual try-ons. This method excels at handling complex and varied hairstyles, maintaining the original identity content and structure while achieving highly detailed and high-fidelity transfer effects.

Sketch2NeRF is a text-to-3D generation framework guided by multi-view sketches. It leverages pre-trained 2D diffusion models (such as Stable Diffusion and ControlNet) to optimize 3D scenes represented by neural radiance fields (NeRF). The method also proposes a novel synchronized generation and reconstruction approach to effectively optimize NeRF. Experiments based on two collected multi-view sketch datasets demonstrate that our method can synthesize consistent 3D content with fine-grained sketch control under high-fidelity text prompts. Extensive results show that our method achieves state-of-the-art performance in terms of sketch similarity and text alignment.