57 مستودعات
Frameworks and methods for guiding video synthesis through specific inputs like poses, trajectories, and camera movements.
Explore 57 awesome GitHub repositories matching part of an awesome list · Controllable Generation. Refine with filters or upvote what's useful.
LivePortrait is a deep learning framework for portrait animation that transfers facial expressions from a driving video to a static image. It functions as an AI motion retargeting tool, mapping movements between different identities while preserving the unique features of the source portrait. The system includes specialized capabilities for cross-species portrait animation, adapting human-centric models to non-human subjects and animals. It also features a motion template generator that converts driving videos into portable files to accelerate inference and protect the identity of the origina
Performs efficient portrait animation with stitching and retargeting.
AnimateAnyone is an appearance-preserving video synthesizer designed for character animation from a single static image. It functions as a diffusion image-to-video generator that transforms a source image into a high-fidelity video sequence while maintaining consistent character identity, clothing, and visual details across all frames. The system enables video-driven character reenactment by transferring motions, facial expressions, and body movements from a reference video onto a static character. It employs pose-guided video generation to control movement via skeleton keypoints and pose sig
Synthesizes consistent and controllable character animations from images.
Champ is a generative vision system and controllable image-to-video generator designed for human image animation. It uses a diffusion-based video synthesizer and 3D parametric guidance to transform a single reference image into a consistent sequence of motion based on external driving data. The framework distinguishes itself through a human pose transfer system that employs 3D body parametric extraction and coordinate-space alignment. This allows the model to map motion from a driving video to a reference person by adjusting for body scales and camera perspectives using depth and semantic con
Animates human images using 3D parametric guidance.
Official Code for MotionCtrl SIGGRAPH 2024
Offers a unified and flexible motion controller for video generation.
CVPR'25Tora: Trajectory-oriented Diffusion Transformer for Video Generation
Uses trajectory-oriented diffusion transformers for video generation.
CVPR 2025 Highlight🔥 Identity-Preserving Text-to-Video Generation by Frequency Decomposition
Maintains identity-preserving text-to-video generation via frequency decomposition.
X-Portrait: Expressive Portrait Animation with Hierarchical Motion Attention You Xie , Hongyi Xu , Guoxian Song , Chao Wang , Yichun Shi , Linjie Luo ByteDance Inc.
Animates expressive portraits using hierarchical motion attention.
CVPR 2025 Consistent and Controllable Image Animation with Motion Diffusion Models
Ensures consistent image animation using motion diffusion models.
Performs training-free video relighting via progressive light fusion.
Generates camera trajectories to act as a virtual director of photography.
Enables human image animation using large-scale video diffusion transformers.
Enables tuning-free trajectory control in video diffusion models.
Identifies and solves conditional image leakage in diffusion models.
Implements self-guided trajectory control for image-to-video generation.
Enables training-free object control using camera poses.
Provides layer-level control for complex animation tasks.
Masters 3D trajectories for multi-entity motion in video generation.
Synchronizes multi-camera video generation from diverse viewpoints.