SpatialEdit Bench SpatialEdit Bench is a comprehensive benchmark dataset for fine grained image spatial editing, introduced in the paper SpatialEdit: Benchmarking Fine Grained Image Spatial Editing. It is designed to evaluate whether an editing model can produce visually plausible results while accurately following spatial transformation instructions. The benchmark covers both object centric and camera centric editing tasks, focusing on precise spatial control rather than just appearance changes. Resources GitHub Repository: EasonXiao 888/SpatialEdit Paper: Hugging Face Papers Training Data: SpatialEdit 500K Model Weights: SpatialEdit 16B Evaluation Scope SpatialEdit Bench is built to assess edits such as: Object Moving: Relocating objects within a scene. Object Rotation: Precise changes in object orientation. Camera Viewpoint Change: Systematic transformations of the camera trajectory and framing. Usage To generate edited outputs for SpatialEdit Bench using the official codebase, you can use the following command structure: Please refer to the GitHub repository for environment setup and further evaluation scripts (camera level and object level). Citation
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