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Geometry-Instructed Video Editing

About

Object-level geometric edits, including translating, rotating, scaling, duplicating, or removing an object, are routine operations in digital content creation (DCC) workflows, yet they remain unreliable in generative video editing. The key challenge lies in specifying the target object's 3D state change unambiguously across viewpoint and time, while consistently updating geometry-dependent secondary effects such as shadows and reflections. We introduce GIVE, a geometry-instructed video editing framework that represents edits through a unified object-state formulation. Two video-aligned geometry streams describe the target object before and after editing: a depth-box encoding coarse 3D placement and extent, and an orientation-box providing an appearance-agnostic orientation cue. Together, these streams provide a compact pre/post geometric specification for object-state transitions. To provide paired supervision for learning these edits, we build a scalable graphics-engine pipeline that executes object-level edit programs and renders controlled before/after pairs, isolating the intended geometric edit while keeping secondary effects consistent with the transformation. Experimental results demonstrate that GIVE produces faithful geometric edits with temporal coherence and consistent secondary effects across operators in a unified framework, and shows promising transfer to in-the-wild videos. Project page: https://geometry-instructed-video-editing.github.io/give/

Chirui Chang, Xiaoyang Lyu, Yi-Hua Huang, Haoru Tan, Shizhen Zhao, Yikang Ding, Jianmin Bao, Xin Tao, Pengfei Wan, Xiaojuan Qi• 2026

Related benchmarks

TaskDatasetResultRank
Video Object RemovalReal-World Videos
Temporal Consistency Score0.991
25
RemovalGIVE-Bench
PSNR27.33
4
Video Object Removal30 Pexels videos approximate clean references via copy-paste protocol (test)
PSNR28.41
4
RotationGIVE-Bench
PSNR21.66
3
RotationReal-video
Temporal Score0.9923
3
ScalingGIVE-Bench
PSNR20.11
3
ScalingReal-video dataset
Temporal Score0.9944
3
TranslationGIVE-Bench
PSNR19.97
3
TranslationReal-video dataset
Temporal Score0.9893
3
DuplicationGIVE-Bench
PSNR19.72
2
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