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AGS-Mesh: Adaptive Gaussian Splatting and Meshing with Geometric Priors for Indoor Room Reconstruction Using Smartphones
Xuqian Ren, Matias Turkulainen, Jiepeng Wang +4
Geometric priors are often used to enhance 3D reconstruction. With many smartphones featuring low-resolution depth sensors and the prevalence of off-the-shelf monocular geometry es…
Reloc3r: Large-Scale Training of Relative Camera Pose Regression for Generalizable, Fast, and Accurate Visual Localization
Siyan Dong, Shuzhe Wang, Shaohui Liu +4
Visual localization aims to determine the camera pose of a query image relative to a database of posed images. In recent years, deep neural networks that directly regress camera po…
DeSplat: Decomposed Gaussian Splatting for Distractor-Free Rendering
Yihao Wang, Marcus Klasson, Matias Turkulainen +3
Gaussian splatting enables fast novel view synthesis in static 3D environments. However, reconstructing real-world environments remains challenging as distractors or occluders brea…
Grouped Discrete Representation for Object-Centric Learning
Rongzhen Zhao, Vivienne Wang, Juho Kannala +1
Object-Centric Learning (OCL) aims to discover objects in images or videos by reconstructing the input. Representative methods achieve this by reconstructing the input as its Varia…
Gaussian Splatting in Mirrors: Reflection-Aware Rendering via Virtual Camera Optimization
Zihan Wang, Shuzhe Wang, Matias Turkulainen +2
Recent advancements in 3D Gaussian Splatting (3D-GS) have revolutionized novel view synthesis, facilitating real-time, high-quality image rendering. However, in scenarios involving…
Multi-Scale Fusion for Object Representation
Rongzhen Zhao, Vivienne Wang, Juho Kannala +1
Representing images or videos as object-level feature vectors, rather than pixel-level feature maps, facilitates advanced visual tasks. Object-Centric Learning (OCL) primarily achi…
Medical Image Segmentation with SAM-generated Annotations
Iira Häkkinen, Iaroslav Melekhov, Erik Englesson +2
The field of medical image segmentation is hindered by the scarcity of large, publicly available annotated datasets. Not all datasets are made public for privacy reasons, and creat…
Sources of Uncertainty in 3D Scene Reconstruction
Marcus Klasson, Riccardo Mereu, Juho Kannala +1
The process of 3D scene reconstruction can be affected by numerous uncertainty sources in real-world scenes. While Neural Radiance Fields (NeRFs) and 3D Gaussian Splatting (GS) ach…
Organized Grouped Discrete Representation for Object-Centric Learning
Rongzhen Zhao, Vivienne Wang, Juho Kannala +1
Object-Centric Learning (OCL) represents dense image or video pixels as sparse object features. Representative methods utilize discrete representation composed of Variational Autoe…
Efficient NeRF Optimization -- Not All Samples Remain Equally Hard
Juuso Korhonen, Goutham Rangu, Hamed R. Tavakoli +1
We propose an application of online hard sample mining for efficient training of Neural Radiance Fields (NeRF). NeRF models produce state-of-the-art quality for many 3D reconstruct…
RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands
Yi Zhao, Le Chen, Jan Schneider +5
It has been a long-standing research goal to endow robot hands with human-level dexterity. Bi-manual robot piano playing constitutes a task that combines challenges from dynamic ta…
Differentiable Product Quantization for Memory Efficient Camera Relocalization
Zakaria Laskar, Iaroslav Melekhov, Assia Benbihi +2
Camera relocalization relies on 3D models of the scene with a large memory footprint that is incompatible with the memory budget of several applications. One solution to reduce the…
Grouped Discrete Representation Guides Object-Centric Learning
Rongzhen Zhao, Vivienne Wang, Juho Kannala +1
Similar to humans perceiving visual scenes as objects, Object-Centric Learning (OCL) can abstract dense images or videos into sparse object-level features. Transformer-based OCL ha…
Dense Road Surface Grip Map Prediction from Multimodal Image Data
Jyri Maanpää, Julius Pesonen, Heikki Hyyti +5
Slippery road weather conditions are prevalent in many regions and cause a regular risk for traffic. Still, there has been less research on how autonomous vehicles could detect sli…
DN-Splatter: Depth and Normal Priors for Gaussian Splatting and Meshing
Matias Turkulainen, Xuqian Ren, Iaroslav Melekhov +3
High-fidelity 3D reconstruction of common indoor scenes is crucial for VR and AR applications. 3D Gaussian splatting, a novel differentiable rendering technique, has achieved state…
Gaussian Splatting on the Move: Blur and Rolling Shutter Compensation for Natural Camera Motion
Otto Seiskari, Jerry Ylilammi, Valtteri Kaatrasalo +5
High-quality scene reconstruction and novel view synthesis based on Gaussian Splatting (3DGS) typically require steady, high-quality photographs, often impractical to capture with…