Open-vocabulary 3D scene segmentation usually assumes RGB-D video, calibrated multi-view imagery, or a reconstructed mesh. GeoSAM-3D studies a lighter setting: a user uploads a short monocular video, clicks or names an object in one frame, and receives a propagated 3D mask over a Gaussian scene. The implementation combines frozen image and video foundation models with a monocular 3D Gaussian Splatting reconstruction and a differentiable graph-geodesic propagation kernel over Gaussian centroids. The central design choice is to propagate prompts by heat-kernel distance on the reconstructed scene graph, rather than by Euclidean nearest neighbors in 3D. This preserves continuity around curved surfaces and reduces leakage across nearby but disconnected objects. This paper describes the repository state, the mathematical kernel implemented in geosam3d.propagate, the feature head trained from Segment Anything masks, and the validation already present in the codebase. The evaluation protocol separates implementation validation, graph propagation quality, leakage control, and interactive latency.
MonoSR: Open-Vocabulary Spatial Reasoning from Monocular Images
Technical University of Munich（慕尼黑工业大学）；A*STAR Institute of Advanced Intelligence and Computing（新加坡科技研究局高级智能与计算研究所）；Singapore University of Technology and Design（新加坡科技设计大学）；Nanyang Technological University（南洋理工大学）
RANGER: A Monocular Zero-Shot Semantic Navigation Framework through Visual Contextual Adaptation
Beihang University（北京航空航天大学）；Beijing Academy of Artificial Intelligence（北京人工智能研究院）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Hangzhou International Innovation Institute, Beihang University（北京航空航天大学杭州国际创新研究院）
WildLIFT: Lifting monocular drone video to 3D for species-agnostic wildlife monitoring
Fondazione Bruno Kessler（布雷诺·科塞勒基金会）；University of Muenster（明斯特大学）；Max Planck Institute of Animal Behaviour（动物行为马克斯·普朗克研究所）；University of Konstanz（康斯坦茨大学）
WildBox: A Dataset and Benchmark for Aerial Monocular 3D Detection of African Savanna Wildlife
D Optical Metrology Unit, Fondazione Bruno Kessler（布鲁诺·凯斯勒基金会3D光学计量部）；Computer Vision and Machine Learning Systems group, Institute for Geoinformatics, University of Muenster（明斯特大学地理信息学研究所计算机视觉与机器学习系统组）；School of Civil, Aerospace and Design Engineering, University of Bristol（布里斯托大学土木、航空航天与设计工程学院）；Department of Biology, University of Southern Denmark（南丹麦大学生物学系）；The Ohio State University（俄亥俄州立大学）；Department of Collective Behavior, Max Planck Institute of Animal Behavior（马克斯·普朗克动物行为研究所集体行为系）；University of Konstanz（康斯坦茨大学）；Centre for the Advanced Study of Collective Behaviour, University of Konstanz（康斯坦茨大学集体行为高级研究中心）；Department of Biology, University of Konstanz（康斯坦茨大学生物学系）；Environmental Computational Science and Earth Observation Laboratory, EPFL（瑞士联邦理工学院环境计算科学与地球观测实验室）
