1 citations · 1 across the 7 of their papers we have counts for
10 papers
ART: Articulated Reconstruction Transformer
Zizhang Li, Cheng Zhang, Zhengqin Li +7
We introduce ART, Articulated Reconstruction Transformer -- a category-agnostic, feed-forward model that reconstructs complete 3D articulated objects from only sparse, multi-state…
DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos
Chieh Hubert Lin, Zhaoyang Lv, Songyin Wu +11
We introduce the Deformable Gaussian Splats Large Reconstruction Model (DGS-LRM), the first feed-forward method predicting deformable 3D Gaussian splats from a monocular posed vide…
Photoreal Scene Reconstruction from an Egocentric Device
Zhaoyang Lv, Maurizio Monge, Ka Chen +5
In this paper, we investigate the challenges associated with using egocentric devices to photorealistic reconstruct the scene in high dynamic range. Existing methodologies typicall…
4DGT: Learning a 4D Gaussian Transformer Using Real-World Monocular Videos
Zhen Xu, Zhengqin Li, Zhao Dong +3
We propose 4DGT, a 4D Gaussian-based Transformer model for dynamic scene reconstruction, trained entirely on real-world monocular posed videos. Using 4D Gaussian as an inductive bi…
Digital Twin Catalog: A Large-Scale Photorealistic 3D Object Digital Twin Dataset
Zhao Dong, Ka Chen, Zhaoyang Lv +14
We introduce the Digital Twin Catalog (DTC), a new large-scale photorealistic 3D object digital twin dataset. A digital twin of a 3D object is a highly detailed, virtually indistin…
Monocular Online Reconstruction with Enhanced Detail Preservation
Songyin Wu, Zhaoyang Lv, Yufeng Zhu +6
We propose an online 3D Gaussian-based dense mapping framework for photorealistic details reconstruction from a monocular image stream. Our approach addresses two key challenges in…
Reading Recognition in the Wild
Charig Yang, Samiul Alam, Shakhrul Iman Siam +12
To enable egocentric contextual AI in always-on smart glasses, it is crucial to be able to keep a record of the user's interactions with the world, including during reading. In thi…
LIRM: Large Inverse Rendering Model for Progressive Reconstruction of Shape, Materials and View-dependent Radiance Fields
Zhengqin Li, Dilin Wang, Ka Chen +11
We present Large Inverse Rendering Model (LIRM), a transformer architecture that jointly reconstructs high-quality shape, materials, and radiance fields with view-dependent effects…
Imaging for All-Day Wearable Smart Glasses
Michael Goesele, Daniel Andersen, Yujia Chen +7
In recent years smart glasses technology has rapidly advanced, opening up entirely new areas for mobile computing. We expect future smart glasses will need to be all-day wearable,…
Learnable Wireless Digital Twins: Reconstructing Electromagnetic Field with Neural Representations
Shuaifeng Jiang, Qi Qu, Xiaqing Pan +3
Fully harvesting the gain of multiple-input and multiple-output (MIMO) requires accurate channel information. However, conventional channel acquisition methods mainly rely on pilot…