5 papers
CORGI: Consistency-Aware 3D Dog Reconstruction from a Single Image in the Wild
Yuxiao Wu, Weile Li, Boyi Zhu +3
Reconstructing high-fidelity 3D models of highly articulated animals, such as dogs, from a single in-the-wild image remains a formidable challenge. In this paper, we introduce CORG…
RenderFormer++: Scalable and Physics-Informed Feed-Forward Neural Rendering
Huangsheng Du, Haoran Zhu, Youcheng Cai +3
We present RenderFormer++, a scalable and physics-informed feed-forward neural rendering framework for global illumination in mesh scenes. Existing Transformer-based neural renderi…
Mesh2GS: White-Box 3DGS Construction via Plenoptic Sampling
Haoran Zhu, Youcheng Cai, Huangsheng Du +2
3D Gaussian Splatting (3DGS) has emerged as a promising method for high-quality, real-time 3D reconstruction. To associate 3DGS with mesh representations, existing methods primaril…
3DGS: Joint Super Sampling and Frame Interpolation for Real-Time Large-Scale 3DGS Rendering
Yibo Zhao, Fan Gao, Youcheng Cai +1
3D Gaussian Splatting (3DGS) enables high-quality real-time 3D rendering but faces challenges in efficiently scaling to ultra-dense scenes and high-resolution due to computational…
STAC: Plug-and-Play Spatio-Temporal Aware Cache Compression for Streaming 3D Reconstruction
Runze Wang, Yuxuan Song, Youcheng Cai +1
Online 3D reconstruction from streaming inputs requires both long-term temporal consistency and efficient memory usage. Although causal variants of VGGT address this challenge thro…