collaborators

12 papers

cs.CV2026

Towards Valid B-Rep Generation: Training-Free Wireframe Anomaly Detection and Repair

Jingyu Wu, Youcheng Cai, Tengyu Luo +1

Multi-stage boundary representation (B-Rep) generation leverages intermediate wireframes to synthesize CAD models. However, geometric and topological risks in these wireframes -- s…

cs.CV2026

StreamSplat: Streaming Feed-Forward 3D Gaussian Splatting

Changhao Song, Yuxuan Wang, Qibiao Li +2

Feed-forward 3D Gaussian Splatting enables efficient novel-view synthesis without per-scene optimization, but most existing methods assume a fixed set of context views and process…

cs.CV2026

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…

cs.GR2026

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…

cs.GR2026

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…

cs.GR2026

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…