Sketch3DVE: Sketch-based 3D-Aware Scene Video Editing
Feng-Lin Liu, Shi-Yang Li, Yan-Pei Cao, Hongbo Fu, Lin Gao
Abstract
Recent video editing methods achieve attractive results in style transfer or appearance modification. However, editing the structural content of 3D scenes in videos remains challenging, particularly when dealing with significant viewpoint changes, such as large camera rotations or zooms. Key challenges include generating novel view content that remains consistent with the original video, preserving unedited regions, and translating sparse 2D inputs into realistic 3D video outputs. To address these issues, we propose Sketch3DVE, a sketch-based 3D-aware video editing method to enable detailed local manipulation of videos with significant viewpoint changes. To solve the challenge posed by sparse inputs, we employ image editing methods to generate edited results for the first frame, which are then propagated to the remaining frames of the video. We utilize sketching as an interaction tool for precise geometry control, while other mask-based image editing methods are also supported. To handle viewpoint changes, we perform a detailed analysis and manipulation of the 3D information in the video. Specifically, we utilize a dense stereo method to estimate a point cloud and the camera parameters of the input video. We then propose a point cloud editing approach that uses depth maps to represent the 3D geometry of newly edited components, aligning them effectively with the original 3D scene. To seamlessly merge the newly edited content with the original video while preserving the features of unedited regions, we introduce a 3D-aware mask propagation strategy and employ a video diffusion model to produce realistic edited videos. Extensive experiments demonstrate the superiority of Sketch3DVE in video editing. Homepage and code: http://http://geometrylearning.com/Sketch3DVE/
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Cited by top-tier papers3
- Lighting-grounded Video Generation with Renderer-based Agent ReasoningZiqi Cai, Taoyu Yang, Zheng Chang, Si Li et al.CVPR 2026 · 3 citations
- SketchDynamics: Exploring Free-Form Sketches for Dynamic Intent Expression in Animation GenerationBoyu Li, Lin-Ping Yuan, Zeyu Wang, Hongbo FuCHI 2026 · 1 citation
- RecEdit-Drive: 3D Reconstruction-Guided Spatiotemporal Video Editing for Autonomous Driving ScenesYipeng Wu, Xin Wang, Chenghan Yang, Chong Wang et al.CVPR 2026
Builds on31
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser et al.CVPR 2022 · 13,123 citations
- Adding Conditional Control to Text-to-Image Diffusion ModelsLvmin Zhang, Anyi Rao, Maneesh AgrawalaICCV 2023 · 6,759 citations
- Depth Anything V2Lihe Yang, Bingyi Kang, Zilong Huang, Zhen Zhao et al.NeurIPS 2024 · 2,305 citations
- Free-Form Image Inpainting With Gated ConvolutionJiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen et al.ICCV 2019 · 1,990 citations
- FateZero: Fusing Attentions for Zero-shot Text-based Video EditingChenyang Qi, Xiaodong Cun, Yong Zhang, Chenyang Lei et al.ICCV 2023 · 510 citations
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