Spatial Context Modeling

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16 papers4 papers in the last four weeks, up 33% on the four weeks before. 0.0% of all new papers.

Look, Reason, Draw a Region: Recursive Refinement for Spatial Context Prediction
Oct 16, 2026Wajeeha Tahir, Anna Tegon, Lionnus Kesting +4Spatial Context Modeling Visual Spatial Reasoning
Integrated Systems Laboratory, ETH Zürich, Switzerland · Pázmány Péter Catholic University, Hungary
MIST: Multi-Scale Spatial Context for Gene Expression Prediction from Histology
Oct 13, 2026Koushik Howlader, Tirtho Roy, Md Tauhidul Islam +1Spatial Context Modeling Spatial Gene Expression Prediction
Iowa State University, Iowa, USA · Stanford University, CA, USA
CartoVec: General-Purpose Location Embeddings from Open Map Data
Oct 12, 2026Furkan GursoyGeospatial Representation Learning Spatial Context Modeling
Learning Holistic Scene Layout against View Shifts in Cross-View Geo-Localization
Oct 9, 2026Chao Yang, Songlian Li, Zhigang TuSpatial Context Modeling Cross-View Geo-Localization
the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, China
Seeing, Saying, but Not Using: From Reportable Spatial Facts to Usable States in Multimodal Large Language Models
Oct 2, 2026Jinchang Zhang, Guoyu LuMultimodal Spatial Reasoning Multimodal Large Language Models
Intelligent Vision and Sensing (IVS) Lab Indiana University Bloomington Bloomington, IN, USA
Network-based Spatial Context Retrieval for Open-weight LLMs: A Faithfulness Benchmark for Grounded Geographic Reasoning
Sep 30, 2026Joan PerezSpatial Reasoning Benchmarks LLM Grounding
Urban Geo Analytics
SpatialSpeak: QA-Native Reconstruction with Local and Global Context for Spatial Chain-of-Thought Reasoning
Sep 27, 2026Yang Cao, Jiaxin Zhang, Dave Zhenyu Chen +4Visual Spatial Reasoning Multi-View 3D Reconstruction
Hong Kong University of Science and Technology · Harbin Institute of Technology · Huawei Noah’s Ark Lab
Continuous Token-Level Spatio-Temporal Context Modeling for Visual Object Tracking
Sep 7, 2026Ding Xia, Meiqin Liu, Jing Zhou +1Spatial Context Modeling Visual Object Tracking
State Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi’an Jiaotong University, Xi’an 710049, China. · College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China. · School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China.
Synergising Local Geo-Environmental Characteristics with Spatial Context for Enhancing Landslide Susceptibility Mapping
Aug 25, 2026Yusen Cheng, Lei Fan, Qinfeng Zhu +3Spatial Context Modeling Landslide Susceptibility Mapping
Department of Civil Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, 215123, China · Department of Geography and Planning, University of Liverpool, Liverpool, L69 3BX, UK · Department of Computer Science, University of Liverpool, Liverpool, L69 3BX, UK +2
CoST: Semantic-Aware Urban Understanding via Spatial-Temporal Alignment
Aug 21, 2026Yutian Jiang, Jiabo Liu, Xixuan Hao +1Geospatial Representation Learning Remote Sensing Image Understanding
The Hong Kong University of Science and Technology (Guangzhou)
PeCA: Palette Context Assisted Inference for Test-Time Paint-Bucket Colourisation on Animation Videos
Aug 2, 2026Dongheng Lin, Jianbo JiaoSpatial Context Modeling
The MIx Group, University of Birmingham, Birmingham, United Kingdom
CoCoSI: Collaborative Cognitive Map Construction for Spatial Intelligence
Jun 9, 2026Yiming Zhang, Ruoxuan Cao, Zhihang ZhongMultimodal Understanding Multimodal Large Language Models
2Cornell University · 1Shanghai Jiao Tong University
The role of spatial context and multitask learning in the detection of organic and conventional farming systems based on Sentinel-2 time series
Mar 25, 2026Jan Hemmerling, Marcel Schwieder, Philippe Rufin +4Spatial Context Modeling Agricultural Remote Sensing
Thünen Earth Observation (ThEO), Thünen Institute of Farm Economics, Braunschweig, Germany. · Earth Observation Lab, Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany. · Earth and Life Institute, UCLouvain, 1348 Louvain-la-Neuve, Belgium. +2
Spatially Aware Deep Learning for Microclimate Prediction from High-Resolution Geospatial Imagery
Feb 27, 2026Idan Sulami, Alon Itzkovitch, Michael R. Kearney +2Spatial Context Modeling Climate Modeling
Tel Aviv University, Faculty of Life Sciences, School of Zoology, Tel Aviv, Israel · School of BioSciences, The University of Melbourne, Melbourne, Victoria, Australia · Tel Aviv University, Center for Artificial Intelligence & Data Science, Tel Aviv, Israel
Resolving Primitive-Sharing Ambiguity in Long-Tailed TLS-Based Industrial MEP Point Cloud Segmentation via Spatial Context Constraints
Jan 27, 2026Chao Yin, Qing Han, Zhiwei Hou +5Class-Imbalanced Learning 3D Point Cloud Segmentation
Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China · School of Geography and Tourism, Hengyang Normal University, Hengyang, China · Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China +3
GeoGR^2:Zero-Shot Geospatial Inference via Geostatistically-Guided Iterative Refinement with LLMs
Aug 6, 2025Jinfan Tang, Kunming Wu, Xieruifeng Gong +4Zero-Shot Learning Geospatial Reasoning
College of Computer Science, Sichuan University · National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University · College of Life Science, Sichuan University

Oct 16, 2026J/K move · Enter open · S save

Look, Reason, Draw a Region: Recursive Refinement for Spatial Context Prediction

Wajeeha Tahir, Anna Tegon, Lionnus Kesting, Gamze İslamoğlu+3

Integrated Systems Laboratory, ETH Zürich, Switzerland · Pázmány Péter Catholic University, Hungary

Spatial Context Modeling Visual Spatial Reasoning Multimodal Spatial Reasoning

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Spatial context prediction requires visual grounding and spatial reasoning to identify vacant regions relative to objects in a scene. Spatial relationships and physical constraints remain challenging for large vision-language models (VLMs). Recursive reasoning has demonstrated strong performance on discrete and abstract reasoning tasks, motivating its use for improving spatial context prediction in natural images. Weight sharing enables higher accuracy with a small trainable parameter count. We introduce Spatial-TRM, a compact recursive model with frozen vision-language features, a convex region decoder, and just 11.2M trainable parameters. This weight-tied reasoner supports six spatial relationships, three reference frames, and open-vocabulary anchor objects. On the RoboSpatial-Home benchmark, Spatial-TRM achieves 29.51% context accuracy, a gain of 9.02 percentage points (44.0% relative) over a separately trained single-step model with the same parameter count. Including the frozen encoders, the model has 877.8M total parameters, approximately

15\times

fewer than the reported 13B size of RoboPoint. These results show that repeated refinement improves spatial context prediction from pretrained vision-language features at a fixed trainable parameter count on this benchmark.