GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation | Paper Citation Record

Observation 66e9850f-65d2-40cd-9607-d3cff592243b · outbound

This paper cites Rotated multi-scale interaction network for referring remote sensing image seg- mentation,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Rotated multi-scale interaction network for referring remote sensing image seg- mentation,

Reference 1

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Observation a1e13361-4b89-46d8-a20c-c2c3c093453d · outbound

This paper cites Cross-Modal Bidirectional Interaction Model for Referring Remote Sensing Image Segmentation.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Cross-Modal Bidirectional Interaction Model for Referring Remote Sensing Image Segmentation

Reference 2

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Observation e1b4fe2f-4312-4348-ac1d-7aa91746d45e · outbound

This paper cites Exploring fine-grained image-text alignment for referring remote sensing image segmentation,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Exploring fine-grained image-text alignment for referring remote sensing image segmentation,

Reference 3

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Observation 4e04466e-b846-46d9-b2d4-af87d29e50cb · outbound

This paper cites Visual programming: Compositional visual reasoning without training,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Visual programming: Compositional visual reasoning without training,

Reference 4

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Observation 5803bbf7-0655-43cd-9b5d-e8f1eca2cd09 · outbound

This paper cites ViperGPT: Visual inference via python execution for reasoning,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation ViperGPT: Visual inference via python execution for reasoning,

Reference 5

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Observation 47f1ba69-7d8d-4c39-9a52-db7f8ff6aba1 · outbound

This paper cites Locate anything on earth: Advancing open-vocabulary object detection for remote sensing community,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Locate anything on earth: Advancing open-vocabulary object detection for remote sensing community,

Reference 6

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Observation 112c7aec-f37b-404f-a8e9-7c1b0d0685b7 · outbound

This paper cites CRIS: CLIP-driven referring image segmentation,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation CRIS: CLIP-driven referring image segmentation,

Reference 7

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Observation 569ad6a7-e90c-4554-88c3-bb7c4ce08b9e · outbound

This paper cites LA VT: Language-aware vision transformer for referring image segmentation,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation LA VT: Language-aware vision transformer for referring image segmentation,

Reference 8

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Observation 200932a1-3c13-43f7-9d0a-bf749a8e991b · outbound

This paper cites Referring image segmentation via recurrent refinement networks,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Referring image segmentation via recurrent refinement networks,

Reference 9

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Observation 5c550ea7-eacd-4e07-9d19-30014bfc951d · outbound

This paper cites Bi-directional relationship inferring network for referring image segmentation,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Bi-directional relationship inferring network for referring image segmentation,

Reference 10

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Observation d8f5fe5f-0509-483d-8210-9f64c1d89501 · outbound

This paper cites Cross-modal pro- gressive comprehension for referring segmentation,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Cross-modal pro- gressive comprehension for referring segmentation,

Reference 11

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Observation 456b6d03-3f99-4fa0-b185-2efa9d891e74 · outbound

This paper cites RRSIS: Referring remote sensing image segmentation,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation RRSIS: Referring remote sensing image segmentation,

Reference 12

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Observation 46241598-3b88-4bfb-91a8-8df0ee3aa9b7 · outbound

This paper cites Referring Remote Sensing Image Segmentation via Bidirectional Alignment Guided Joint Prediction.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Referring Remote Sensing Image Segmentation via Bidirectional Alignment Guided Joint Prediction

Reference 13

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Observation 4ee71596-a81d-4a70-b9a2-919058af988b · outbound

This paper cites RSRefSeg 2: Decoupling referring remote sensing image segmentation with founda- tion models,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation RSRefSeg 2: Decoupling referring remote sensing image segmentation with founda- tion models,

Reference 14

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Observation 34e9f8d8-06db-4df6-a684-a9d0fd91fe0a · outbound

This paper cites Zero-shot referring remote sensing image segmentation with expert knowledge priors and hierarchical relational matching,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Zero-shot referring remote sensing image segmentation with expert knowledge priors and hierarchical relational matching,

Reference 15

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Observation 5386f454-e589-4722-bd13-c52ebfaa4157 · outbound

This paper cites RSVG-ZeroOV: Exploring a training-free framework for zero-shot open-vocabulary visual grounding in remote sensing images,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation RSVG-ZeroOV: Exploring a training-free framework for zero-shot open-vocabulary visual grounding in remote sensing images,

Reference 16

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Observation 783d56ff-fe4f-4e8e-a4cd-9ba7c0e3c6fa · outbound

This paper cites DGL-RSIS: Decou- pling global spatial context and local class semantics for training-free remote sensing image segmentation,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation DGL-RSIS: Decou- pling global spatial context and local class semantics for training-free remote sensing image segmentation,

Reference 17

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Observation d882258c-c5c1-416b-8630-ef0dd9c5e9d1 · outbound

This paper cites SAM 3: Segment Anything with Concepts.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation SAM 3: Segment Anything with Concepts

Reference 18

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Observation c9858861-d33d-428d-a6af-b71d4da10b93 · outbound

This paper cites SegEarth-OV: Towards training-free open-vocabulary segmentation for remote sensing images,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation SegEarth-OV: Towards training-free open-vocabulary segmentation for remote sensing images,

Reference 19

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Observation fcd9b6be-570b-4d75-b9c2-fbf09530504f · outbound

This paper cites SegEarth-OV3: Exploring SAM 3 for open-vocabulary semantic seg- mentation in remote sensing images,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation SegEarth-OV3: Exploring SAM 3 for open-vocabulary semantic seg- mentation in remote sensing images,

Reference 20

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Observation adbf840c-3227-4c3b-b55e-ba296417f2dd · outbound

This paper cites InstructSAM: A training-free framework for instruction-oriented remote sensing object recognition,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation InstructSAM: A training-free framework for instruction-oriented remote sensing object recognition,

Reference 21

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Observation ad8b33cf-c6cb-4884-8f80-8de4c5b4b3e7 · outbound

This paper cites SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model

Reference 22

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Observation 53a278df-2956-40a3-abd5-a24d8a118c03 · outbound

This paper cites GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding

Reference 23

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Observation 313523de-42e9-49b5-944d-e298fa4085cd · outbound

This paper cites Text4Seg++: Advancing image segmentation via generative lan- guage modeling,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Text4Seg++: Advancing image segmentation via generative lan- guage modeling,

Reference 24

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Observation a73058b5-63db-47e4-989b-15a3a1bd2250 · outbound

This paper cites Enabling training-free text-based remote sensing segmentation,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Enabling training-free text-based remote sensing segmentation,

Reference 25

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Observation 7a9302ee-4474-42e9-a186-2d8cea68aca2 · outbound

This paper cites Neural module networks,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Neural module networks,

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Observation 8efe472f-2d7b-4b67-aa13-9e4159feb1d0 · outbound

This paper cites Neural-symbolic VQA: Disentangling reasoning from vision and lan- guage understanding,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Neural-symbolic VQA: Disentangling reasoning from vision and lan- guage understanding,

Reference 27

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Observation 837d3780-9d85-4ed1-862d-6c0040c120de · outbound

This paper cites The neuro- symbolic concept learner: Interpreting scenes, words, and sentences from natural supervision,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation The neuro- symbolic concept learner: Interpreting scenes, words, and sentences from natural supervision,

Reference 28

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Observation 54e048cc-7d42-4f0b-939b-840842c44d57 · outbound

This paper cites ReCLIP: A strong zero-shot baseline for referring ex- pression comprehension,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation ReCLIP: A strong zero-shot baseline for referring ex- pression comprehension,

Reference 29

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Observation 527cd1be-e8da-484a-9e09-b2181f86da54 · outbound

This paper cites A new way to represent the relative position between areal objects,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation A new way to represent the relative position between areal objects,

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Observation e3dc5ef3-9819-4333-bc5e-3ff608c6ce5a · outbound

This paper cites Fuzzy spatial relationships for image processing and inter- pretation: a review,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Fuzzy spatial relationships for image processing and inter- pretation: a review,

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Observation f2512c7d-41d8-43e9-9655-de2702b2e506 · outbound

This paper cites Grounding spatial language in perception: An empirical and computational investigation,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Grounding spatial language in perception: An empirical and computational investigation,

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Observation 4f5468a3-b34e-4507-bf4e-1b278ff6d13a · outbound

This paper cites STAR: A first- ever dataset and a large-scale benchmark for scene graph generation in large-size satellite imagery,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation STAR: A first- ever dataset and a large-scale benchmark for scene graph generation in large-size satellite imagery,

Reference 33

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Observation 85bf0af1-8813-44fd-b21a-fe34c6bfc4b5 · outbound

This paper cites ReCon1M: A large-scale benchmark dataset for relation comprehension in remote sensing imagery,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation ReCon1M: A large-scale benchmark dataset for relation comprehension in remote sensing imagery,

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Observation 0ad1b1ac-5f22-40b3-9972-1bf0055555d3 · outbound

This paper cites AUG: A New Dataset and An Efficient Model for Aerial Image Urban Scene Graph Generation.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation AUG: A New Dataset and An Efficient Model for Aerial Image Urban Scene Graph Generation

Reference 35

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Observation e7acb938-e474-4efd-ae3e-322cc3705dc7 · outbound

This paper cites RSGround-R1: Rethinking remote sensing visual grounding through spatial reasoning,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation RSGround-R1: Rethinking remote sensing visual grounding through spatial reasoning,

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Observation b8d0fa98-7ded-42d3-b027-1db51fdf14dd · outbound

This paper cites ProVG: Progressive visual grounding via language decoupling for remote sensing imagery,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation ProVG: Progressive visual grounding via language decoupling for remote sensing imagery,

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Observation 0d5f8765-4740-4384-9050-388528f5ddfd · outbound

This paper cites Grounded language-image pre- training,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Grounded language-image pre- training,

Reference 38

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Observation 25ea5a75-5c03-473c-950c-8f0a5cdaf240 · outbound

This paper cites Grounding DINO: Marrying DINO with grounded pre-training for open-set object detection,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Grounding DINO: Marrying DINO with grounded pre-training for open-set object detection,

Reference 39

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Observation c14f8b06-1ec6-4dd7-9e4b-ab83d9256433 · outbound

This paper cites RS5M and GeoRSCLIP: A large-scale vision-language dataset and a large vision-language model for remote sensing,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation RS5M and GeoRSCLIP: A large-scale vision-language dataset and a large vision-language model for remote sensing,

Reference 40

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Observation e64276ee-1bcb-42c5-ad4f-d69e04da772d · outbound

This paper cites RemoteCLIP: A vision language foundation model for remote sensing,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation RemoteCLIP: A vision language foundation model for remote sensing,

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Observation aed72f14-ba23-408b-95dc-1ed5c3c7b7f3 · outbound

This paper cites SkyScript: A large and semantically diverse vision-language dataset for remote sens- ing,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation SkyScript: A large and semantically diverse vision-language dataset for remote sens- ing,

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Observation a219296b-5a1b-4c51-8386-f5d0906ecc1c · outbound

This paper cites Segment anything,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Segment anything,

Reference 43

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Observation 66977964-9578-429d-9c0d-9aca96e95814 · outbound

This paper cites SAM 2: Segment anything in images and videos,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation SAM 2: Segment anything in images and videos,

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Observation b983ecab-65bb-4a31-826d-eb9b01d09738 · outbound

This paper cites RemoteSAM: Towards segment anything for earth observation,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation RemoteSAM: Towards segment anything for earth observation,

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Observation 42b7739d-14b9-4e6e-818b-e49a0e2e40d1 · outbound

This paper cites Qwen3 Technical Report.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Qwen3 Technical Report

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Observation 27bbc58f-2371-4369-b323-fbf42c4024f1 · outbound

This paper cites Slicing aided hyper inference and fine-tuning for small object detection,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Slicing aided hyper inference and fine-tuning for small object detection,

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Observation a322e578-7976-48ac-b5a0-0944f900980e · outbound

This paper cites Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs

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Observation 7f7d0ce1-10a0-49ab-9a8c-4081b5c640a1 · outbound

This paper cites Falcon Mamba: The First Competitive Attention-free 7B Language Model.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Falcon Mamba: The First Competitive Attention-free 7B Language Model

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Observation f77d11f8-15c9-45d8-a7f8-957d1c818b12 · outbound

This paper cites The Llama 3 Herd of Models.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation The Llama 3 Herd of Models

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Observation adb5a19c-2a18-4f19-a3f1-169b74930662 · outbound

This paper cites CARIS: Context-aware referring image segmentation,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation CARIS: Context-aware referring image segmentation,

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Observation 457128f5-d7b9-4569-8843-924b9f92f9e7 · outbound

This paper cites Generalized re- ferring expression segmentation on aerial photos,.

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation Generalized re- ferring expression segmentation on aerial photos,

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