DF3DV-1K supplies 1,048 scenes with clean and cluttered image pairs plus a challenging 41-scene subset to benchmark and improve distractor-free radiance field methods.
ACM Transactions on Graphics (TOG)44(6), 1–16 (2025)
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GlobalSplat achieves competitive novel-view synthesis on RealEstate10K and ACID using only 16K Gaussians via global scene tokens and coarse-to-fine training, with a 4MB footprint and under 78ms inference.
FluSplat trains a model with geometric alignment constraints on multi-view edits to produce consistent 3D scene edits from sparse views in a single forward pass without test-time optimization.
SpectralSplat disentangles appearance from geometry in feed-forward 3D Gaussian Splatting by factoring color into base and adapted streams conditioned on DINOv2 embeddings, trained on paired data from a hybrid relighting pipeline.
SyncFix improves 3D reconstructions by synchronizing multi-view latent representations in a diffusion refinement process, generalizing from pair-wise training to arbitrary view counts at inference.
citing papers explorer
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DF3DV-1K: A Large-Scale Dataset and Benchmark for Distractor-Free Novel View Synthesis
DF3DV-1K supplies 1,048 scenes with clean and cluttered image pairs plus a challenging 41-scene subset to benchmark and improve distractor-free radiance field methods.
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GlobalSplat: Efficient Feed-Forward 3D Gaussian Splatting via Global Scene Tokens
GlobalSplat achieves competitive novel-view synthesis on RealEstate10K and ACID using only 16K Gaussians via global scene tokens and coarse-to-fine training, with a 4MB footprint and under 78ms inference.
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FluSplat: Sparse-View 3D Editing without Test-Time Optimization
FluSplat trains a model with geometric alignment constraints on multi-view edits to produce consistent 3D scene edits from sparse views in a single forward pass without test-time optimization.
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SpectralSplat: Appearance-Disentangled Feed-Forward Gaussian Splatting for Driving Scenes
SpectralSplat disentangles appearance from geometry in feed-forward 3D Gaussian Splatting by factoring color into base and adapted streams conditioned on DINOv2 embeddings, trained on paired data from a hybrid relighting pipeline.
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SyncFix: Fixing 3D Reconstructions via Multi-View Synchronization
SyncFix improves 3D reconstructions by synchronizing multi-view latent representations in a diffusion refinement process, generalizing from pair-wise training to arbitrary view counts at inference.