# Animation Generation

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.

Animate-X is a universal animation framework based on LDM, designed for various character types (collectively termed X), including humanoid characters. This framework enhances motion representation by introducing pose indicators, allowing for a more comprehensive capture of motion patterns from driving videos. The primary advantages of Animate-X include in-depth modeling of motion and the ability to understand motion patterns in driving videos, applying them flexibly to target characters. Additionally, Animate-X introduces the Animated Anthropomorphic Benchmark (A2Bench) to evaluate its performance on universal and widely applicable animated images.

Eggnog is a video production-focused website that allows users to create characters with unique faces and outfits, and then use these characters to generate animated videos. By combining artificial intelligence technology, it simplifies and enhances the video production process. It provides a user-friendly interface for dragging and dropping characters onto storyboards and automatically generating videos. This technology not only boosts the efficiency of video production but also lowers the threshold for entry into the field, making it easier for non-professionals to create video content.

CharacterGen is an efficient 3D character generation framework that can generate high-quality and consistent-looking 3D character meshes from a single input image. Using a streamlined generation pipeline and an image-conditioned multi-view diffusion model, it effectively aligns the input pose to a standard form while preserving key attributes from the input image, addressing challenges posed by diverse poses. It also employs a transformer-based universal sparse view reconstruction model and a texture back-projection strategy to generate high-quality texture maps.

L4GM is a 4D large-scale reconstruction model that can quickly generate animated objects from single-view video input. It utilizes a novel dataset comprising multi-view videos showcasing animated objects rendered in Objaverse. This dataset includes 44K distinct objects and 110K animations, rendered from 48 viewpoints, generating 12M videos encompassing a total of 300M frames. L4GM is built upon the pre-trained 3D large reconstruction model LGM, which can output 3D Gaussian ellipsoids from multi-view image input. L4GM outputs a 3D Gaussian Splatting representation for each frame, subsequently upsampled to a higher frame rate for temporal smoothing. Moreover, L4GM incorporates time-self attention layers to assist in learning temporal consistency and utilizes multi-view rendering loss at each timestep for model training.

Follow-Your-Click is a tool that produces open-domain regional image animations from short prompts. Users can click to participate in the animation generation process and view and compare different generation methods and their effects. The tool showcases the animation results and compares them with those of other latest open-source animation methods and commercial tools, demonstrating the comparative effectiveness of animation generation. Additionally, by demonstrating our motion strength control and ablation studies, users can understand the strengths and weaknesses of our method compared to others.