From the 1 of 12 linked papers with an AI index.
12 papers
Wonder: Video World Model Done Better
Jiacong Xu, Hanwen Jiang, Zhixin Shu +3
Wonder is a video world model that lets users explore a generated scene in real time by moving a virtual camera, using a dense coordinate conditioning and a sparse attention memory…
SPEAR: A Simulator for Photorealistic Embodied AI Research
Mike Roberts, Renhan Wang, Rushikesh Zawar +10
Interactive simulators have become powerful tools for training embodied agents and generating synthetic visual data, but existing photorealistic simulators suffer from limited gene…
LooseControlVideo: Directorial Video Control using Spatial Blocking
Shariq Farooq Bhat, Niloy J. Mitra, Kalyan Sunkavalli
Precise 3D spatial orchestration in text-to-video generation remains a significant challenge, particularly for multi-object scenes where semantic layout and temporal dynamics are o…
OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation
Yuheng Liu, Xin Lin, Xinke Li +9
Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthe…
E-RayZer: Self-supervised 3D Reconstruction as Spatial Visual Pre-training
Qitao Zhao, Hao Tan, Qianqian Wang +5
Self-supervised pre-training has driven rapid progress in foundation models for language, 2D images, and video, yet remains largely unexplored for learning 3D-aware representations…
tttLRM: Test-Time Training for Long Context and Autoregressive 3D Reconstruction
Chen Wang, Hao Tan, Wang Yifan +6
We propose tttLRM, a novel large 3D reconstruction model that leverages a Test-Time Training (TTT) layer to enable long-context, autoregressive 3D reconstruction with linear comput…