Skip to content
Preprint

Streaming4D: Accelerate 4D World Models via Block-wise Video Generation and Incremental Reconstruction

Sep 2026 · 0 citations · 49 references
Computer Science

TL;DR

This work proposes Streaming4D, a tightly coupled synchronous pipeline that integrates block-wise autoregressive video generation with incremental 3D reconstruction, and instantiates it using a Self-Forcing-style autoregressive generator and an incremental reconstruction backend.

Abstract

Current 4D generation paradigms are often bottlenecked by a sequential decoupling design: video is generated first, followed by 3D reconstruction, leading to high interaction latency. This limits applications in interactive real-time scenarios. To this end, we propose \textbf{Streaming4D}, a tightly coupled synchronous pipeline that integrates block-wise autoregressive video generation with incremental 3D reconstruction. Unlike traditional frame-by-frame emission and delayed geometry recovery, Streaming4D generates temporal video blocks and immediately triggers reconstruction for each completed block, enabling parallel execution between synthesis and geometric updates. This approach allows the world representation to evolve online with the video stream, reducing feedback latency while preserving geometric fidelity. We instantiate \textbf{Streaming4D} using a Self-Forcing-style autoregressive generator and an incremental reconstruction backend. Experiments show consistent runtime improvements across resolutions on a single RTX 4090 (1.24$\times$ speedup), while maintaining high-quality 4D geometry and multi-view consistency.

View source

Similar papers

Preprint Oct 2026

DynStream: Online Streaming 4D Gaussian Reconstruction of Dynamic Worlds from Unposed Video

Online reconstruction of dynamic 4D scenes from long, unposed streaming videos requires both continuous processing and photorealistic rendering, which existing methods struggle to achieve simultaneously. Existing feed-forward Gaussian methods are restricted to offline processing, whereas online point-cloud approaches s...

Ding-Wei Xian, Xiao-Yu Zhou, Ya-Jiao Xiong et al. · 0 citations
Preprint Sep 2026

DecoGS: Adaptive Static-Dynamic Decoupling of 3D Gaussians for Free-Viewpoint Video Streaming

DecoGS introduces an adaptive mechanism that selectively focuses optimization on spatiotemporal regions exhibiting motion or photometric changes, eliminating redundant updates that cause flickering and drift in nominally static regions, while enabling fast, high-fidelity scene updates.

Idil Sulo, Alexey Supikov, Ilke Demir et al. · 0 citations
Preprint Oct 2026

High-Throughput Generative Video Super-Resolution on a Single Consumer GPU

Generative video super-resolution (VSR) can recover visually compelling high-frequency detail by leveraging diffusion priors, but iterative sampling and heavy spatio-temporal coupling make practical deployments difficult. We study a different operating point: practical HD generative VSR on a single high-end consumer GP...

Georgios Panaretou, S. Chatzis · 0 citations
Preprint Sep 2026

FastVR: Efficient Streaming Video Restoration with One-Step Diffusion

FastVR is presented, a streaming video restoration framework built on a one-step diffusion model, which delivers strong restoration quality and temporal consistency while processing 1080p video at 11 FPS on a single H20 GPU.

Xiao-Xu Chen, Qin Yang, Hao-Ran Bai et al. · 0 citations
Preprint Aug 2026

Revisiting Local Context for Long-Horizon Streaming 3D Reconstruction

ABot-Recon is presented, a simple streaming model that caches KV features from only the preceding 11 frames and predicts a point map in the current camera coordinate system together with an adjacent-frame relative pose that remains equivariant under changes of reference frame.

Jiarong Han, Jincheng Xiong, Yu-Zhou Liu et al. · 2 citations · ⚡1
Preprint Oct 2026

RenderBench: Benchmarking Render-to-Real Video Transfer with Reconstructed Digital Twins

This work introduces RenderBench, a benchmark of 12 reconstructed real-world scenes spanning large-scale indoor environments and egocentric viewpoints, with both static and dynamic settings, and provides paired real observations and editable scene state for assessing both appearance fidelity and preservation of geometr...

Di-Cong Qiu, Zhi-Yuan Xu, Yao Liu et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.