20 papers · ranked by Valyu relevance
Jiadong Zhang, Wei Wang, Yingbai Hu, Chao Zeng + 2 more
'Alois Christian Knoll' 'Shu Li'] Active mapping is an important technique for mobile robots to autonomously explore and recognize indoor environments. View planning, as the core of active mapping, determines the quality of the map and the efficiency of exploration. However, most current view-planning methods focus on…
Ziwei Liao, Binbin Xu, Steven L. Waslander
Priors Authors: ['Ziwei Liao' 'Binbin Xu' 'Steven L. Waslander'] Abstract: Object-level mapping builds a 3D map of objects in a scene with detailed shapes and poses from multi-view sensor observations. Conventional methods struggle to build complete shapes and estimate accurate poses due to partial occlusions and…
Edith Langer, Timothy Patten, Markus Vincze
Detecting changes such as moved, removed, or new objects is the essence for numerous indoor applications in robotics such as tidying-up, patrolling, and fetch/carry tasks. The problem is particularly challenging in open-world scenarios where novel objects may appear at any time. The main idea of this paper is to detect…
Han Xiao, Houxuan Liu, Yunchao Ding, Yang Lu
—Accurate perception of objects in the environment is important for improving the scene understanding capability of SLAM systems. In robotic and augmented reality applications, object maps with semantic and metric information show attractive advantages. In this paper, we present RO-MAP, a novel multiobject mapping…
Merle Stahl, Lena J. Straßer, Chit Tong Lio, Judith Bernett + 2 more
Single-cell RNA sequencing (scRNA-seq) provides comprehensive gene expression data at a single-cell level but lacks spatial context. In contrast, spatial transcriptomics captures both spatial and transcriptional information but is limited by resolution, sensitivity, or feasibility. No single technology combines both…
Guoqing Jiang, Saiya Li, Ziyu Huang, Guorong Cai + 2 more
Point clouds are highly regarded in the field of 3D object detection for their superior geometric properties and versatility. However, object occlusion and defects in scanning equipment frequently result in sparse and missing data within point clouds, adversely affecting the final prediction. Recognizing the…
Lukas Schmid, Jeffrey Delmerico, Johannes L. Schönberger, Juan Nieto + 3 more
'Marc Pollefeys' 'Roland Siegwart' 'César Cadena'] Abstract— For robotic interaction in environments shared with other agents, access to volumetric and semantic maps of the scene is crucial. However, such environments are inevitably subject to long-term changes, which the map needs to account for. We thus propose…
O. Contier, C.I. Baker, M.N. Hebart
Object vision is commonly thought to involve a hierarchy of brain regions processing increasingly complex image features, with high-level visual cortex supporting object recognition and categorization. However, object vision supports diverse behavioral goals, suggesting basic limitations of this category-centric…
Zhian Chen, Yaqi Hu, Yong Liu, Theodore Brown
Existing visual SLAM systems with neural representations excel in static scenes but fail in dynamic environments where moving objects degrade performance. To address this, we propose a robust dynamic SLAM framework combining classic geometric features for localization with learned photometric features for dense…
Krzysztof Zieliński, Dominik Belter
— In this article, we propose a new keyframe-based mapping system. The proposed method updates local Normal Distribution Transform maps (NDT) using data from an RGB-D sensor. The cells of the NDT are stored in 2D view-dependent structures to better utilize the properties and uncertainty model of RGB-D cameras. This…
Zhihe Zhang, Hao Wei, Hongtao Nie
— Simultaneous localization and mapping, as a fundamental task in computer vision, has gained higher demands for performance in recent years due to the rapid development of autonomous driving and unmanned aerial vehicles. Traditional SLAM algorithms highly rely on basic geometry features such as points and lines, which…
Qianqian Wang, Junhao Song, Chenxi Du, Chen Wang + 1 more
Real-world understanding serves as a medium that bridges the information world and the physical world, enabling the realization of virtual-real mapping and interaction. However, scene understanding based solely on 2D images faces problems such as a lack of geometric information and limited robustness against occlusion.…
Benjamin Ries, Irfan Alibay, David W H Swenson, Hannah M Baumann + 3 more
Relative binding free energy (RBFE) calculations have emerged as a powerful tool supporting ligand optimization in drug discovery. Despite many successes, the use of RBFEs can often be limited by automation problems, in particular the setup of such calculations. Atom mapping algorithms are an essential component in…
Thomas Chabal, Shizhe Chen, Jean Ponce, Cordelia Schmid
This paper addresses the problem of reconstructing a scene online at the level of objects given an RGB-D video sequence. While current object-aware neural implicit representations hold promise, they are limited in online reconstruction efficiency and shape completion. Our main contributions to alleviate the above…
Sanjar Adilov
Machine learning models for molecular-property prediction typically work with molecular representations in the form of fingerprints, descriptors, or graphs. In case of fingerprints and descriptors, molecular representations usually comprise thousands of features, which causes the curse of dimensionality for many…
Xinyu Zhou, Pengtao Dang, Haixu Tang, Laura Xianlu Peng + 6 more
Spatial transcriptomics (ST) data demands models that recover how associations among molecular and cellular features change across tissue while contending with noise, collinearity, cell mixing, and thousands of predictors. We present Spatially Smooth Sparse Regression (S3R), a general framework that estimates…
J. Almeida, S. Kristensen, Z. Tal, A. Fracasso
Understanding how object information is neurally organized is fundamental to unravel object recognition^1–4^. The best-known neural organizational principle of information is topographical mapping of specific dimensions. Such maps have been shown mainly for sensorimotor information within sensorimotor cortices (e.g.…
Mary Pitman, David Hahn, Gary Tresadern, David Mobley
Drug discovery is accelerated with computational methods such as alchemical simulations to estimate ligand affinities. In particular, relative binding free energy (RBFE) simulations are beneficial for lead optimization. To use RBFE simulations to compare prospective ligands in silico, researchers first plan the…
Wiete Fehner, Morgan Fogarty, Jerry Tang, Dana Wilhelm + 6 more
Understanding how the brain represents meaning in real-world contexts is essential for both fundamental neuroscience and clinical applications. Brain encoding and decoding models from naturalistic stimuli provide a powerful window into semantic representations. Yet, existing approaches rely on a constrained scanning…
A. Kidder, G. L. Quek, T. Grootswagers
How is object information organized in high-level visual cortex? Recently, a comprehensive model of object space in macaques was proposed, defined by the orthogonal axes of animacy and aspect ratio (2). However, when using stimuli that dissociated category, animacy, and aspect ratio in humans, no tuning of aspect ratio…