Pith. sign in

REVIEW 4 cited by

WonderTurbo: Generating Interactive 3D World in 0.72 Seconds

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2504.02261 v1 pith:CSN4XJCW submitted 2025-04-03 cs.CV

classification cs.CV
keywords generationwonderturboappearancegeometricinteractivesecondsconsistencydepth
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation

    cs.RO 2026-07 conditional novelty 6.0 of 10

    Long-horizon action-faithful consistency, not short-term visual realism, dominates world-model reliability for robot policy evaluation; GigaWorld-1 implements that roadmap and gains 14.9% on evaluator-alignment metrics.

  2. WonderFree: Enhancing Novel View Quality and Cross-View Consistency for 3D Scene Exploration

    cs.CV 2025-06 conditional novelty 6.0 of 10

    A pipeline that restores corrupted novel-view videos with a video diffusion model and jointly denoises multiple viewpoints to improve 3D scene exploration from a single image.

  3. EmbodieDreamer: Advancing Real2Sim2Real Transfer for Policy Training via Embodied World Modeling

    cs.RO 2025-07 conditional novelty 5.0 of 10

    A Real2Sim2Real framework that aligns simulator dynamics via differentiable parameter fitting and renders photorealistic policy-training videos with a diffusion model, improving real-world manipulation success.

  4. DriveGen3D: Boosting Feed-Forward Driving Scene Generation with Efficient Video Diffusion

    cs.CV 2025-10 conditional novelty 4.0 of 10

    DriveGen3D makes long driving-video synthesis and 3D scene reconstruction practical by caching only the conditional diffusion branch, quantizing cross-view attention, and fusing temporal context into a feed-forward Ga...

Pith tools