16 citations · 29 across the 11 of their papers we have counts for
13 papers · 1 filter
Unblur-SLAM: Dense Neural SLAM for Blurry Inputs
Qi Zhang, Denis Rozumny, Francesco Girlanda +4
We propose Unblur-SLAM, a novel RGB SLAM pipeline for sharp 3D reconstruction from blurred image inputs. In contrast to previous work, our approach is able to handle different type…
Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding
Yue Li, Qi Ma, Runyi Yang +8
While 3DGS has emerged as a high-fidelity scene representation, encoding rich, general-purpose features directly from its primitives remains under-explored. We address this gap by…
IDSplat: Instance-Decomposed 3D Gaussian Splatting for Driving Scenes
Carl Lindström, Mahan Rafidashti, Maryam Fatemi +3
Reconstructing dynamic driving scenes is essential for developing autonomous systems through sensor-realistic simulation. Although recent methods achieve high-fidelity reconstructi…
ProDyG: Progressive Dynamic Scene Reconstruction via Gaussian Splatting from Monocular Videos
Shi Chen, Erik Sandström, Sandro Lombardi +2
Achieving truly practical dynamic 3D reconstruction requires online operation, global pose and map consistency, detailed appearance modeling, and the flexibility to handle both RGB…
SceneSplat++: A Large Dataset and Comprehensive Benchmark for Language Gaussian Splatting
Mengjiao Ma, Qi Ma, Yue Li +10
3D Gaussian Splatting (3DGS) serves as a highly performant and efficient encoding of scene geometry, appearance, and semantics. Moreover, grounding language in 3D scenes has proven…
Gaussian Mapping for Evolving Scenes
Vladimir Yugay, Thies Kersten, Luca Carlone +3
Mapping systems with novel view synthesis (NVS) capabilities, most notably 3D Gaussian Splatting (3DGS), are widely used in computer vision, as well as in various applications, inc…