Experiments show that StreamSplat remains competitive with state-of-the-art feed-forward 3DGS methods under sparse causal inputs, despite not using future views or full-scene context, and scales to long input streams with 256, 512, and 1024 views where fixed-view baselines run out of memory, yielding sustained improvem...
Changhao Song, Yuxuan Wang, Qi-Biao Li et al.· 0 citations
AnyGS2Mesh is presented, the first feed-forward framework for directly reconstructing 3D meshes from 3D Gaussian Splatting representations with support for arbitrary input image resolutions, and demonstrates the potential of combining Gaussian representations and feed-forward Transformer architectures for scalable 3D g...
Yuxuan Song, Fan Gao, Yi-Bo Zhao et al.· 0 citations
LightBridge is presented, a feed-forward generative framework for controllable relighting of complete 3DGS assets in a single pass and efficient single-pass prediction of complete relit 3DGS assets without scene-specific optimization.
Heng Cao, Pan-Hao Cheng, Huang-Sheng Du et al.· 0 citations
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