Video AI Tools

SceneScape can generate long videos of different scenes from text prompts and camera angles. It ensures 3D consistency by building a unified mesh of the scene, allowing for realistic walkthroughs in places like spaceships and caves.

Shape-aware Text-driven Layered Video Editing can edit the shape of objects in videos while keeping them consistent across frames. It uses a text-conditioned diffusion model to achieve this, making video editing more effective than other methods.

Tune-A-Video can generate videos from a single text-video pair by fine-tuning text-to-image diffusion models. It lets users change subjects, backgrounds, and styles while keeping the video content consistent.

MAGVIT can perform video synthesis tasks like inpainting, outpainting, and generating animations from single images. It is much faster than other models, working 100 times quicker than diffusion models and 60 times faster than autoregressive models, while also achieving the best results on multiple benchmarks.

MotionBERT can recover 3D human motion from noisy 2D observations. It excels in 3D pose estimation, action recognition, and motion prediction, achieving the lowest pose estimation error when trained from scratch.

VToonify can create high-quality artistic portrait videos from images. It allows for controllable style transfer on non-aligned faces and produces smooth, coherent videos with flexible controls on color and intensity.

MCVD can generate videos and predict future and past frames using a masked conditional score-based diffusion model. It achieves high quality and diversity in generated frames, excelling in various video synthesis tasks.