WonderTurbo: Generating Interactive 3D World in 0.72 Seconds
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Abstract (arXiv)
Interactive 3D generation is gaining momentum and capturing extensive attention for its potential to create immersive virtual experiences. However, a critical challenge in current 3D generation technologies lies in achieving real-time interactivity. To address this issue, we introduce WonderTurbo, the first real-time interactive 3D scene generation framework capable of generating novel perspectives of 3D scenes within 0.72 seconds. Specifically, WonderTurbo accelerates both geometric and appearance modeling in 3D scene generation. In terms of geometry, we propose StepSplat, an innovative method that constructs efficient 3D geometric representations through dynamic updates, each taking only 0.26 seconds. Additionally, we design QuickDepth, a lightweight depth completion module that provides consistent depth input for StepSplat, further enhancing geometric accuracy. For appearance modeling, we develop FastPaint, a 2-steps diffusion model tailored for instant inpainting, which focuses on maintaining spatial appearance consistency. Experimental results demonstrate that WonderTurbo achieves a remarkable 15X speedup compared to baseline methods, while preserving excellent spatial consistency and delivering high-quality output.
Key facts. Cited by 32 papers in the map (data through 14 Oct 2026). Builds on 67 of its 81 references that are in the map. First posted on arXiv 3 Apr 2025.
Builds on
67 of 81 references.
References · 67
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- 2023Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstructioncited by 759
- 2023pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstructioncited by 684
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- 2023Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levelscited by 503
- 2019SynSin: End-to-end View Synthesis from a Single Imagecited by 364
- 2024DepthSplat: Connecting Gaussian Splatting and Depthcited by 286
- 2020Single-View View Synthesis with Multiplane Imagescited by 263
- 2023DriveDreamer: Towards Real-world-driven World Models for Autonomous Drivingcited by 261
- 2024No Pose, No Problem: Surprisingly Simple 3D Gaussian Splats from Sparse Unposed Imagescited by 248
- 2023Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Modelscited by 245
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- 2024Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splattingcited by 221
- 20203D Photography using Context-aware Layered Depth Inpaintingcited by 206
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- 2024InFusion: Inpainting 3D Gaussians via Learning Depth Completion from Diffusion Priorcited by 56
50 most cited of 67 All 67 (JSON)
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Citing papers per year: 2025: 18; 2026: 14.
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