GeoFlip is a new benchmark for video generation models that tests their ability to produce physically correct outcomes when the initial geometry of a scene is altered. The benchmark presents 482 pairs of scenes with controlled changes in extent, placement, and mechanism configuration, and evaluates models on event correctness, structural integrity, and similarity to reference videos. Across 16 evaluated models, the best event correctness averaged only 27.98%, highlighting significant gaps in geometry‑sensitive physical reasoning.
By Yuqi Li, Junming Liu, Bowen Hu, Ruize Niu, Huiran Duan, Yingli Tian, Hao Wu
Orbia is a new benchmark that systematically evaluates 3D consistency in interactive video world models. It organizes evaluation into three dimensions—input preservation, generated‑content persistence, and 3D self‑consistency—using controlled exploration and revisit protocols. The benchmark covers 720 instances across indoor and outdoor scenes and tests 27 different models, providing a comprehensive framework for diagnosing and improving 3D consistency.
By Dongyue Lu, Guian Fang, Hur Lim, Yonggang Wu, Yanrong Wang, Hongshan Chen, Shengju Qian, Yue Liao, Wei Chow, Lingdong Kong, Tianxin Huang, Yu Yang, Hongji Yang, Junchao Huang, Ao Liang, Yihao Wang, Zihan Wang, Rong Li, Hanlin Chen, Xin Wang, Wei Tsang Ooi, Mike Zheng Shou, Shuicheng Yan
arXiv:2608. 09594v1 Announce Type: cross Abstract: Recently, AI-driven video generation has attracted considerable attention.
By Yifei Xue, Yuanchen Fei, Hao Zhang, Chenzhi Nie, Tie ji, Yizhen Lao
OmniShowcase introduces a method for generating omnidirectional videos of a specific subject from a handful of multi‑view images. It combines an automated data‑synthesis pipeline that creates training videos with diverse camera trajectories driven by the subject’s geometry, and a geometry‑conditioning technique that supplies the model with surface‑normal maps reconstructed from the reference views. The authors release Showcase‑4K, a large corpus of 3D‑asset‑based videos with 12 camera motions and 88 trajectory configurations, and ShowcaseBench, a held‑out evaluation set with source meshes and camera parameters.
By Junyeong Ahn, Geonwoo Kim, Kinam Kim, Gihwi Kim, Hoonjin Jung, Hyojin Jang, Jaegul Choo
arXiv:2610.08684v1 Announce Type: new
Abstract: Modern video models can generate realistic videos from real appearance references and proxy renders that specify scene structure, viewpoint changes, an...
By Dicong Qiu, Zhiyuan Xu, Yaosheng Liu, Feng Han, Bo Ye
Recently, AI-driven video generation has attracted considerable attention. This surge increases the demand for reliable video quality assessment (VQA) metrics to evaluate AI-generated content (AIGC) videos and guide model optimization.
arXiv:2610.08791v1 Announce Type: new
Abstract: Video world models can produce visually convincing yet physically inconsistent sequences, raising concerns about their reliability for prediction and p...
By Mingju Gao, Qingle Liu, Yuzhao Peng, Xinjie Lin, Ziming Qin, Zheng Jiang, Wenyi Li, Calvin Xiao, Youjie Zheng, Kaisen Yang, Qinhuai Na
arXiv:2609.35052v2 Announce Type: replace-cross
Abstract: Video world models must preserve the visual state of the world over time, but existing evaluation protocols often rely on generated histories...
By Hao Wang, Tao Yu, Liuzhou Zhang, HeXin Wang, Haopeng Jin, Yuxuan Zhou, Xinming Wang, Hongzhu Yi, Xinye Li, Yuanlei Wang, Ping Nie, Yan Huang, Yuxuan Zhang, Pengfei Zhou, Yanyan Zou, Wei Yang
TourPhysics is an online framework that builds physics‑grounded visual world models from a single image and a declarative physical configuration. It integrates deterministic simulation with video generation, separating simulator state, geometric evidence, generator controls, and appearance memory to produce consistent observations for exploration and manipulation. The system preserves the input scene, follows prescribed camera and object trajectories more closely than baselines, and reduces appearance drift during long‑horizon revisits.
By Xin Zhang, Yabo Chen, Zixuan Duan, Haibin Huang, Chi Zhang, Feng Xu, Xuelong Li
RoboPhys-3D is a 3D‑grounded embodied world model benchmark built on RoboTwin 2.0, featuring 50 manipulation tasks, 5,000 episodes, and 25,000 multi‑view ground‑truth videos. It evaluates video world models by processing both generated and ground‑truth videos through the same 3D reconstruction pipeline, allowing the separation of reconstruction‑induced from generation‑induced errors. The benchmark defines 50 metrics across four sub‑dimensions—pixel fidelity, 3D geometry consistency, state understanding, and task completeness—and introduces the Average Full Score and RoboPhyscore for holistic assessment, with RoboPhyscore showing strong correlation with human judgments.
By Tianyi Wang, Jiazhou Chen, Yiming Xu, Xiangyu Li, Tianyi Zeng, Chih-Hsien Chou, Ning Lu, Liang Peng, Junfeng Jiao, Christian Claudel
arXiv:2610.29936v1 Announce Type: new
Abstract: Recovering metric world-space hand motion from egocentric video supports understanding human interactions and transferring them to embodied agents. Thr...
By Naru Suzuki, Satoshi Ikehata, Takehiko Ohkawa, Yoichi Sato, Shuhei Kurita
arXiv:2606. 28128v1 Announce Type: cross Abstract: Video generation models have emerged as a promising paradigm for embodied world simulation.
By Peiwen Zhang, Yufan Deng, Shangkun Sun, Juncheng Ma, Duomin Wang, Jonas Du, Zilin Pan, Ye Huang, Hao Liang, Songyan Huang, Ruihua Zhang, Enze Xie, Ming-Yu Liu, Daquan Zhou