3 citations · 8 across the 13 of their papers we have counts for
13 papers · 1 filter
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…
SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture
Haiwen Diao, Penghao Wu, Hanming Deng +55
Recent large vision-language models (VLMs) remain fundamentally constrained by a persistent dichotomy: understanding and generation are treated as distinct problems, leading to fra…
MonoArt: Progressive Structural Reasoning for Monocular Articulated 3D Reconstruction
Haitian Li, Haozhe Xie, Junxiang Xu +3
Reconstructing articulated 3D objects from a single image requires jointly inferring object geometry, part structure, and motion parameters from limited visual evidence. A key diff…
Bridging Semantic and Kinematic Conditions with Diffusion-based Discrete Motion Tokenizer
Chenyang Gu, Mingyuan Zhang, Haozhe Xie +3
Prior motion generation largely follows two paradigms: continuous diffusion models that excel at kinematic control, and discrete token-based generators that are effective for seman…
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…
InfiniteDance: Scalable 3D Dance Generation Towards in-the-wild Generalization
Ronghui Li, Zhongyuan Hu, Li Siyao +6
Although existing 3D dance generation methods perform well in controlled scenarios, they often struggle to generalize in the wild. When conditioned on unseen music, existing method…
3D Scene Generation: A Survey
Haozhe Xie, Beichen Wen, Zhaoxi Chen +2
3D scene generation seeks to synthesize spatially structured, semantically meaningful, and photorealistic environments for applications such as immersive media, robotics, autonomou…
Compositional Generative Model of Unbounded 4D Cities
Haozhe Xie, Zhaoxi Chen, Fangzhou Hong +1
3D scene generation has garnered growing attention in recent years and has made significant progress. Generating 4D cities is more challenging than 3D scenes due to the presence of…
DynamicCity: Large-Scale 4D Occupancy Generation from Dynamic Scenes
Hengwei Bian, Lingdong Kong, Haozhe Xie +3
Urban scene generation has been developing rapidly recently. However, existing methods primarily focus on generating static and single-frame scenes, overlooking the inherently dyna…
3DTopia-XL: Scaling High-quality 3D Asset Generation via Primitive Diffusion
Zhaoxi Chen, Jiaxiang Tang, Yuhao Dong +10
The increasing demand for high-quality 3D assets across various industries necessitates efficient and automated 3D content creation. Despite recent advancements in 3D generative mo…
CrowdMoGen: Zero-Shot Text-Driven Collective Motion Generation
Yukang Cao, Xinying Guo, Mingyuan Zhang +3
While recent advances in text-to-motion generation have shown promising results, they typically assume all individuals are grouped as a single unit. Scaling these methods to handle…
Generative Gaussian Splatting for Unbounded 3D City Generation
Haozhe Xie, Zhaoxi Chen, Fangzhou Hong +1
3D city generation with NeRF-based methods shows promising generation results but is computationally inefficient. Recently 3D Gaussian Splatting (3D-GS) has emerged as a highly eff…
CityDreamer: Compositional Generative Model of Unbounded 3D Cities
Haozhe Xie, Zhaoxi Chen, Fangzhou Hong +1
3D city generation is a desirable yet challenging task, since humans are more sensitive to structural distortions in urban environments. Additionally, generating 3D cities is more…