StateCraft introduces a new architecture that separates a persistent, updatable abstract state from the visual state in video world models. By pairing a language model with a video diffusion model, it tracks entity changes over time and conditions visual generation on this abstract state. The approach is evaluated on generative interfaces and a new benchmark, showing improved generation quality, memory usage, and controllability, while enabling direct editing of unseen states and extending to spatial 3D environments.
By Lorenzo Venturoli, Nedko Savov, Xi Wang, Marc Pollefeys, Luc Van Gool
The paper introduces 4DGS-WAM, an object‑centric world action model that uses a 4D Gaussian Splatting representation to separate dynamic objects from a static background. By predicting future actions of dynamic actors and their Gaussian splat transformations, the model can reuse previously observed static content for future state generation, reducing redundant background processing. Experiments on the KITTI‑MOT dataset demonstrate the model’s ability to perform short‑horizon prediction and past reconstruction.
By Yueen Ma, Zenglin Xu, Irwin King
arXiv:2610.07958v1 Announce Type: new
Abstract: Feed-forward 3D Gaussian Splatting (3DGS) reconstructs a scene in a single forward pass, replacing per-scene optimization with a network trained across...
By Minhyeok Lee, Jungho Lee, Minseok Kang, Heeseung Choi, Ig-Jae Kim, Sangyoun Lee
BoxWorld introduces a novel approach to real‑time interactive video worlds by decoupling interaction reasoning from generative rendering. A coding agent builds a Box World Engine that applies user‑defined rules to determine interaction outcomes and exposes object states via a lightweight interface of layout boxes, persistent attributes, and dynamic status variables. A separate Box‑State Generative Renderer then autoregressively renders these evolving states into video, enabling online control over object motion, state switches, and conditional events. The system employs a three‑stage training strategy—learning object grounding from open‑domain videos, state transitions from gameplay videos, and rollout distillation on self‑generated histories—to handle real‑time state updates while maintaining visual coherence. BoxWorld outperforms end‑to‑end world models and remains competitive across multiple public benchmarks, with a new PairedStateBench benchmark for fine‑grained interaction control.
By Zike Wu, Ahmed Hatem, Chintan Trivedi, Wallace Michel Pinto Lira, Xuebin Qin, Lele Wang, Renjie Liao
arXiv:2608.23549v1 Announce Type: new
Abstract: Rendering views using 3D scene representations such as Gaussian Splatting (3DGS), Neural Radiance Fields (NeRF), meshes, or even point clouds produces...
By Khiem Vuong, Deva Ramanan, Srinivasa Narasimhan
3DGS-HPC is a framework that improves 3D Gaussian Splatting for novel view synthesis by mitigating transient distractors such as moving objects and varying shadows. It combines a patch‑wise classification strategy that uses local spatial consistency for robust region‑level decisions with a hybrid classification metric that adaptively integrates photometric and perceptual cues. Experiments show that this approach outperforms existing methods in reducing distractor effects and enhancing 3DGS quality.
By Jiahao Chen, Yipeng Qin, Ganlong Zhao, Xin Li, Wenping Wang, Guanbin Li
arXiv:2610.02160v1 Announce Type: new
Abstract: Precise control over camera and object motion is essential for professional video production. Existing methods control objects only coarsely, through i...
By Wei Cao, Hao Zhang, Vikram Voleti, Yuqun Wu, Mallikarjun B R, Shimon Vainer, Mark Boss, Yaoyao Liu
arXiv:2609.10540v1 Announce Type: new
Abstract: Recent video world models generate increasingly realistic and interactive visual experiences, yet lack reliable mechanisms for maintaining persistent w...
By Zheng-Hui Huang, Guixu Lin, Jiacheng Lin, Yi-Chuan Huang, Ruihan Yu, Muyao Niu, Siqi Yang, Yu-Lun Liu, Yung-Yu Chuang, Kaipeng Zhang, Zhixiang Wang
Feed-forward 3D Gaussian Splatting enables efficient novel-view synthesis without per-scene optimization, but most existing methods assume a fixed set of context views and process them jointly. This limits their applicability to online scenarios where calibrated views arrive sequentially and the scene must be updated causally.
arXiv:2610.28631v1 Announce Type: new
Abstract: Current world models for explicit world simulation typically follow two distinct pathways: (1) video generative models (e.g., Sora), which simulate rea...
By Weiqi Zhang, Wenyuan Zhang, Yu-Shen Liu, Junsheng Zhou
arXiv:2610.17625v1 Announce Type: cross
Abstract: For video generation in dynamic world modeling, observed static and dynamic content should be efficiently reused to provide conditions for repeated g...
By Jianhui Zhang, Zuyao Lin, Pengxin Xu, Jingdong Wang, Xingyu Chen
arXiv:2610.25395v2 Announce Type: replace
Abstract: Turning a moving-camera perspective video into a 360{\deg} video means generating content outside the input frame under several constraints: observ...
By Michael Wakeham, Mrinmoy Kumar Das, Wenqi Wang, Ayush Tewari, Boqing Gong, Deepti Ghadiyaram