🚨 Paper Alert 🚨
➡️Paper Title: MagicMotion: Controllable Video Generation with Dense-to-Sparse Trajectory Guidance
🌟Few pointers from the paper
🎯Recent advances in video generation have led to remarkable improvements in visual quality and temporal coherence.
🎯Upon this, trajectory-controllable video generation has emerged to enable precise object motion control through explicitly defined spatial paths.
🎯However, existing methods struggle with complex object movements and multi-object motion control, resulting in imprecise trajectory adherence, poor object consistency, and compromised visual quality.
🎯Furthermore, these methods only support trajectory control in a single format, limiting their applicability in diverse scenarios.
🎯Additionally, there is no publicly available dataset or benchmark specifically tailored for trajectory-controllable video generation, hindering robust training and systematic evaluation.
🎯To address these challenges, authors of this paper introduced “MagicMotion”, a novel image-to-video generation framework that enables trajectory control through three levels of conditions from dense to sparse: masks, bounding boxes, and sparse boxes.
🎯Given an input image and trajectories, MagicMotion seamlessly animates objects along defined trajectories while maintaining object consistency and visual quality.
🎯Furthermore, they presented “MagicData”, a large-scale trajectory-controlled video dataset, along with an automated pipeline for annotation and filtering.
🎯They also introduce “MagicBench”, a comprehensive benchmark that assesses both video quality and trajectory control accuracy across different numbers of objects.
🎯Extensive experiments demonstrate that MagicMotion outperforms previous methods across various metrics.
🏢Organization:
@FudanUniversity ,
@MSFTResearch Asia
🧙Paper Authors: Quanhao Li, Zhen Xing, Rui Wang, Hui Zhang, Qi Dai, Zuxuan Wu
📝 Read the Full Paper here:
arxiv.org/abs/2503.16421
🗂️ Project Page:
quanhaol.github.io/magicmoti…
🧑💻 Code:
github.com/quanhaol/MagicMot…
🎥 Be sure to watch the attached Demo Video - Sound on 🔊🔊
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