4 citations · 16 across the 19 of their papers we have counts for
24 papers
GenRec: Knowing Where to Reconstruct and Where to Generate
Ata Çelen, Jaewoo Jung, Federico Tombari +4
Generative novel view synthesis from sparse input images is rarely all reconstruction or all generation: pixels visible in some source view have a unique correct value modulated on…
PointDiT: Pixel-Space Diffusion for Monocular Geometry Estimation
Haofei Xu, Rundi Wu, Philipp Henzler +7
State-of-the-art single-image 3D reconstruction methods often rely on complex hybrid architectures and loss functions, or compress geometry into latent spaces in order to leverage…
AugSplat: Radiance Field-Informed Gaussian Splatting for Sparse-View Settings
Lorenzo Lazzaroni, Riccardo Bollati, Daniel Barath +2
Generating high-quality novel views at real-time frame rates remains a central challenge in 3D vision, particularly in sparse-view scenarios. Neural radiance fields have demonstrat…
DynaTok: Token-Based 4D Reconstruction from Partial Point Clouds
Weirong Chen, Keisuke Tateno, Hidenobu Matsuki +3
We address 4D reconstruction from partial point cloud sequences, where depth-sensor observations are incomplete, unordered, and lack explicit temporal correspondences. This geometr…
OpenGaFF: Open-Vocabulary Gaussian Feature Field with Codebook Attention
Kunyi Li, Michael Niemeyer, Sen Wang +3
Understanding open-vocabulary 3D scenes with Gaussian-based representations remains challenging due to fragmented and spatially inconsistent semantic predictions across multi-view…
DiskChunGS: Large-Scale 3D Gaussian SLAM Through Chunk-Based Memory Management
Casimir Feldmann, Maximum Wilder-Smith, Vaishakh Patil +4
Recent advances in 3D Gaussian Splatting (3DGS) have demonstrated impressive results for novel view synthesis with real-time rendering capabilities. However, integrating 3DGS with…
SING3R-SLAM: Submap-based Indoor Monocular Gaussian SLAM with 3D Reconstruction Priors
Kunyi Li, Michael Niemeyer, Sen Wang +3
Recent advances in dense 3D reconstruction have demonstrated strong capability in accurately capturing local geometry. However, extending these methods to incremental global recons…
Learning Neural Exposure Fields for View Synthesis
Michael Niemeyer, Fabian Manhardt, Marie-Julie Rakotosaona +5
Recent advances in neural scene representations have led to unprecedented quality in 3D reconstruction and view synthesis. Despite achieving high-quality results for common benchma…
OracleGS: Grounding Generative Priors for Sparse-View Gaussian Splatting
Atakan Topaloglu, Kunyi Li, Michael Niemeyer +3
Sparse-view novel view synthesis is fundamentally ill-posed due to severe geometric ambiguity. Current methods are caught in a trade-off: regressive models are geometrically faithf…
CausNVS: Autoregressive Multi-view Diffusion for Flexible 3D Novel View Synthesis
Xin Kong, Daniel Watson, Yannick Strümpler +2
Multi-view diffusion models have shown promise in 3D novel view synthesis, but most existing methods adopt a non-autoregressive formulation. This limits their applicability in worl…
3D-LATTE: Latent Space 3D Editing from Textual Instructions
Maria Parelli, Michael Oechsle, Michael Niemeyer +2
Despite the recent success of multi-view diffusion models for text/image-based 3D asset generation, instruction-based editing of 3D assets lacks surprisingly far behind the quality…
GALA: Guided Attention with Language Alignment for Open Vocabulary Gaussian Splatting
Elena Alegret, Kunyi Li, Sen Wang +5
3D scene reconstruction and understanding have gained increasing popularity, yet existing methods still struggle to capture fine-grained, language-aware 3D representations from 2D…
Masks make discriminative models great again!
Tianshi Cao, Marie-Julie Rakotosaona, Ben Poole +2
We present Image2GS, a novel approach that addresses the challenging problem of reconstructing photorealistic 3D scenes from a single image by focusing specifically on the image-to…
LODGE: Level-of-Detail Large-Scale Gaussian Splatting with Efficient Rendering
Jonas Kulhanek, Marie-Julie Rakotosaona, Fabian Manhardt +5
In this work, we present a novel level-of-detail (LOD) method for 3D Gaussian Splatting that enables real-time rendering of large-scale scenes on memory-constrained devices. Our ap…
Learning Efficient Fuse-and-Refine for Feed-Forward 3D Gaussian Splatting
Yiming Wang, Lucy Chai, Xuan Luo +5
Recent advances in feed-forward 3D Gaussian Splatting have led to rapid improvements in efficient scene reconstruction from sparse views. However, most existing approaches construc…
SuperGSeg: Open-Vocabulary 3D Segmentation with Structured Super-Gaussians
Siyun Liang, Sen Wang, Kunyi Li +5
3D Gaussian Splatting has recently gained traction for its efficient training and real-time rendering. While its vanilla representation is mainly designed for view synthesis, recen…
Gaussians-to-Life: Text-Driven Animation of 3D Gaussian Splatting Scenes
Thomas Wimmer, Michael Oechsle, Michael Niemeyer +1
State-of-the-art novel view synthesis methods achieve impressive results for multi-view captures of static 3D scenes. However, the reconstructed scenes still lack "liveliness," a k…
MonoGSDF: Exploring Monocular Geometric Cues for Gaussian Splatting-Guided Implicit Surface Reconstruction
Kunyi Li, Michael Niemeyer, Zeyu Chen +2
Accurate meshing from monocular images remains a key challenge in 3D vision. While state-of-the-art 3D Gaussian Splatting (3DGS) methods excel at synthesizing photorealistic novel…
Splat-SLAM: Globally Optimized RGB-only SLAM with 3D Gaussians
Erik Sandström, Keisuke Tateno, Michael Oechsle +4
3D Gaussian Splatting has emerged as a powerful representation of geometry and appearance for RGB-only dense Simultaneous Localization and Mapping (SLAM), as it provides a compact…
OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views
Francis Engelmann, Fabian Manhardt, Michael Niemeyer +3
Large visual-language models (VLMs), like CLIP, enable open-set image segmentation to segment arbitrary concepts from an image in a zero-shot manner. This goes beyond the tradition…
RadSplat: Radiance Field-Informed Gaussian Splatting for Robust Real-Time Rendering with 900+ FPS
Michael Niemeyer, Fabian Manhardt, Marie-Julie Rakotosaona +7
Recent advances in view synthesis and real-time rendering have achieved photorealistic quality at impressive rendering speeds. While Radiance Field-based methods achieve state-of-t…
InseRF: Text-Driven Generative Object Insertion in Neural 3D Scenes
Mohamad Shahbazi, Liesbeth Claessens, Michael Niemeyer +4
We introduce InseRF, a novel method for generative object insertion in the NeRF reconstructions of 3D scenes. Based on a user-provided textual description and a 2D bounding box in…
UniSDF: Unifying Neural Representations for High-Fidelity 3D Reconstruction of Complex Scenes with Reflections
Fangjinhua Wang, Marie-Julie Rakotosaona, Michael Niemeyer +3
Neural 3D scene representations have shown great potential for 3D reconstruction from 2D images. However, reconstructing real-world captures of complex scenes still remains a chall…
DNS SLAM: Dense Neural Semantic-Informed SLAM
Kunyi Li, Michael Niemeyer, Nassir Navab +1
In recent years, coordinate-based neural implicit representations have shown promising results for the task of Simultaneous Localization and Mapping (SLAM). While achieving impress…