TRACE: Object Motion Editing in Videos with First-Frame Trajectory Guidance

2026-03-26

AI Summary

This work addresses the challenge of controllably editing the motion trajectory of a target object in videos while preserving the original scene content. To this end, the authors propose a two-stage framework: first, a cross-view motion transformation module maps a user-specified trajectory—provided only in the initial frame—into per-frame bounding boxes that account for camera motion; second, a motion-conditioned video resynthesis module generates the object along this trajectory while maintaining background consistency. By eliminating the need for complex point-trajectory inputs, the method significantly enhances user-friendliness and temporal coherence. Experiments demonstrate that the approach produces more realistic, temporally consistent, and controllable motion edits on diverse real-world videos compared to existing image-to-video or video-to-video methods.

Technology Category

• Computer Vision: Motion & Tracking
• Intelligent Robots: Motion and Path Planning
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

We study object motion path editing in videos, where the goal is to alter a target object's trajectory while preserving the original scene content. Unlike prior video editing methods that primarily manipulate appearance or rely on point-track-based trajectory control, which is often challenging for users to provide during inference, especially in videos with camera motion, we offer a practical, easy-to-use approach to controllable object-centric motion editing. We present Trace, a framework that enables users to design the desired trajectory in a single anchor frame and then synthesizes a temporally consistent edited video. Our approach addresses this task with a two-stage pipeline: a cross-view motion transformation module that maps first-frame path design to frame-aligned box trajectories under camera motion, and a motion-conditioned video re-synthesis module that follows these trajectories to regenerate the object while preserving the remaining content of the input video. Experiments on diverse real-world videos show that our method produces more coherent, realistic, and controllable motion edits than recent image-to-video and video-to-video methods.

Problem

• object motion editing
• video editing
• trajectory guidance
• camera motion
• motion path

Innovation

• trajectory editing
• object motion control
• video re-synthesis
• camera motion handling
• first-frame guidance