Flux-GS is a mobile-optimized 3D Gaussian Splatting method that compresses specular energy via Monte Carlo aggregation, recovers details with attribute-conditioned SH offsets, and uses multi-view guidance for densification to cut parameters while keeping visual quality.
Vtnet: Visual trans- former network for object goal navigation.arXiv preprint arXiv:2105.09447
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
SAGE-Nav decouples LLM global planning from reactive control via hierarchical scene graphs and alignment fusion, reporting SOTA results on i-THOR and RoboTHOR with improved efficiency and zero-shot generalization.
PLMD applies a denoising diffusion model to predict labels for unknown map regions, allowing goal localization in unexplored environments by substituting completed labels into existing navigation pipelines.
citing papers explorer
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Monte Carlo Energy Aggregation for Mobile 3D Gaussian Splatting
Flux-GS is a mobile-optimized 3D Gaussian Splatting method that compresses specular energy via Monte Carlo aggregation, recovers details with attribute-conditioned SH offsets, and uses multi-view guidance for densification to cut parameters while keeping visual quality.
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SAGE-Nav: Leveraging LLM Planning and Alignment Fusion for Hierarchical Scene Graph-Guided Navigation
SAGE-Nav decouples LLM global planning from reactive control via hierarchical scene graphs and alignment fusion, reporting SOTA results on i-THOR and RoboTHOR with improved efficiency and zero-shot generalization.
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Plug-and-Play Label Map Diffusion for Universal Goal-Oriented Navigation
PLMD applies a denoising diffusion model to predict labels for unknown map regions, allowing goal localization in unexplored environments by substituting completed labels into existing navigation pipelines.