14 papers
Has GPT-6-Astra Achieved Embodied Intelligence?
SenseNova, Joint Research Team, : +60
GPT-6-Astra demonstrates a level of competence in robotic manipulation and navigation that challenges the conventional paradigm of building specialized models for individual tasks…
VBVR-Pro: A Scalable and Verifiable Suite for Native Visual Reasoning
Junxiang Xu, Ruisi Wang, Fanyi Pu +49
Native visual reasoning treats visual generation as the medium of reasoning itself: visual states (i.e. images and videos) are not merely inputs to be understood or outputs to be r…
ACE-Data-0: Human-Centric Ambient Capture as Embodied Data Engine
Yukang Cao, Haozhe Xie, Beichen Wen +13
Embodied intelligence faces a fundamental data bottleneck. Models must capture how first-person perception, whole-body motion, dexterous manipulation, object state, sound, and touc…
PhysX-Omni: Unified Simulation-Ready Physical 3D Generation for Rigid, Deformable, and Articulated Objects
Ziang Cao, Yinghao Liu, Haitian Li +5
Simulation-ready physical 3D assets have emerged as a promising direction owing to their broad applicability in downstream tasks. However, most existing 3D generation methods eithe…
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…
OnlineSI: Taming Large Language Model for Online 3D Understanding and Grounding
Zixian Liu, Zhaoxi Chen, Liang Pan +1
In recent years, researchers have increasingly been interested in how to enable Multimodal Large Language Models (MLLM) to possess spatial understanding and reasoning capabilities.…
PhysX-Anything: Simulation-Ready Physical 3D Assets from Single Image
Ziang Cao, Fangzhou Hong, Zhaoxi Chen +2
3D modeling is shifting from static visual representations toward physical, articulated assets that can be directly used in simulation and interaction. However, most existing 3D ge…
Scaling Spatial Intelligence with Multimodal Foundation Models
Zhongang Cai, Ruisi Wang, Chenyang Gu +26
Despite remarkable progress, multimodal foundation models still exhibit surprising deficiencies in spatial intelligence. In this work, we explore scaling up multimodal foundation m…
3D and 4D World Modeling: A Survey
Lingdong Kong, Yu Yang, Jianbiao Mei +20
World modeling has become a cornerstone in AI research, enabling agents to understand, represent, and predict the dynamic environments they inhabit. While prior work largely emphas…
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…
EgoTwin: Dreaming Body and View in First Person
Jingqiao Xiu, Fangzhou Hong, Yicong Li +5
While exocentric video synthesis has achieved great progress, egocentric video generation remains largely underexplored, which requires modeling first-person view content along wit…
Collaborative Multi-Modal Coding for High-Quality 3D Generation
Ziang Cao, Zhaoxi Chen, Liang Pan +1
3D content inherently encompasses multi-modal characteristics and can be projected into different modalities (e.g., RGB images, RGBD, and point clouds). Each modality exhibits dist…
PhysX-3D: Physical-Grounded 3D Asset Generation
Ziang Cao, Zhaoxi Chen, Liang Pan +1
3D modeling is moving from virtual to physical. Existing 3D generation primarily emphasizes geometries and textures while neglecting physical-grounded modeling. Consequently, despi…