From the 1 of 7 linked papers with an AI index.
7 papers
ACE-Data-0: Human-Centric Ambient Capture as Embodied Data Engine
Yukang Cao, Haozhe Xie, Beichen Wen +13
The paper presents ACE, a data collection system that records synchronized multimodal streams—including egocentric and multi-view video, full-body and hand motion, object geometry,…
WorldLens: Full-Spectrum Evaluations of Driving World Models in Real World
Ao Liang, Lingdong Kong, Tianyi Yan +19
Generative world models are reshaping embodied AI, enabling agents to synthesize realistic 4D driving environments that look convincing but often fail physically or behaviorally. D…
Is Your Driving World Model an All-Around Player?
Lingdong Kong, Ao Liang, Tianyi Yan +20
Today's driving world models can generate remarkably realistic dash-cam videos, yet no single model excels universally. Some generate photorealistic textures but violate basic phys…
HSImul3R: Physics-in-the-Loop Reconstruction of Simulation-Ready Human-Scene Interactions
Yukang Cao, Haozhe Xie, Fangzhou Hong +4
We present HSImul3R, a unified framework for simulation-ready 3D reconstruction of human-scene interactions (HSI) from casual captures, including sparse-view images and monocular v…
4DNeX: Feed-Forward 4D Generative Modeling Made Easy
Zhaoxi Chen, Tianqi Liu, Long Zhuo +6
We present 4DNeX, the first feed-forward framework for generating 4D (i.e., dynamic 3D) scene representations from a single image. In contrast to existing methods that rely on comp…
Hi3DEval: Advancing 3D Generation Evaluation with Hierarchical Validity
Yuhan Zhang, Long Zhuo, Ziyang Chu +5
Despite rapid advances in 3D content generation, quality assessment for the generated 3D assets remains challenging. Existing methods mainly rely on image-based metrics and operate…