2 citations · 4 across the 19 of their papers we have counts for
16 papers · 1 filter
PnP-U3D: Plug-and-Play 3D Framework Bridging Autoregression and Diffusion for Unified Understanding and Generation
Yongwei Chen, Tianyi Wei, Yushi Lan +4
The rapid progress of large multimodal models has inspired efforts toward unified frameworks that couple understanding and generation. While such paradigms have shown remarkable su…
4RC: 4D Reconstruction via Conditional Querying Anytime and Anywhere
Yihang Luo, Shangchen Zhou, Yushi Lan +2
We present 4RC, a unified feed-forward framework for 4D reconstruction from monocular videos. Unlike existing approaches that typically decouple motion from geometry or produce lim…
Video4Spatial: Towards Visuospatial Intelligence with Context-Guided Video Generation
Zeqi Xiao, Yiwei Zhao, Lingxiao Li +6
We investigate whether video generative models can exhibit visuospatial intelligence, a capability central to human cognition, using only visual data. To this end, we present Video…
ArtiLatent: Realistic Articulated 3D Object Generation via Structured Latents
Honghua Chen, Yushi Lan, Yongwei Chen +1
We propose ArtiLatent, a generative framework that synthesizes human-made 3D objects with fine-grained geometry, accurate articulation, and realistic appearance. Our approach joint…
STream3R: Scalable Sequential 3D Reconstruction with Causal Transformer
Yushi Lan, Yihang Luo, Fangzhou Hong +7
We present STream3R, a novel approach to 3D reconstruction that reformulates pointmap prediction as a decoder-only Transformer problem. Existing state-of-the-art methods for multi-…
FastMesh: Efficient Artistic Mesh Generation via Component Decoupling
Jeonghwan Kim, Yushi Lan, Armando Fortes +2
Recent mesh generation approaches typically tokenize triangle meshes into sequences of tokens and train autoregressive models to generate these tokens sequentially. Despite substan…