OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning | Paper Citation Record

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This paper cites Qwen2.5-VL Technical Report.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Qwen2.5-VL Technical Report

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This paper cites Graph of thoughts: Solving elaborate problems with large language models.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Graph of thoughts: Solving elaborate problems with large language models

Reference 2

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This paper cites Zero-shot semantic segmentation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Zero-shot semantic segmentation

Reference 3

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This paper cites Universeg: Universal medical image segmentation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Universeg: Universal medical image segmentation

Reference 4

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This paper cites Coco-stuff: Thing and stuff classes in context.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Coco-stuff: Thing and stuff classes in context

Reference 5

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This paper cites Open-vocabulary Panoptic Segmentation with Embedding Modulation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Open-vocabulary Panoptic Segmentation with Embedding Modulation

Reference 6

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This paper cites Cat-seg: Cost aggregation for open-vocabulary semantic segmentation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Cat-seg: Cost aggregation for open-vocabulary semantic segmentation

Reference 7

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This paper cites The cityscapes dataset for semantic urban scene understanding.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning The cityscapes dataset for semantic urban scene understanding

Reference 8

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This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 9

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This paper cites Decoupling zero-shot semantic segmentation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Decoupling zero-shot semantic segmentation

Reference 10

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This paper cites Open-Vocabulary Universal Image Segmentation with MaskCLIP.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Open-Vocabulary Universal Image Segmentation with MaskCLIP

Reference 11

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This paper cites The pascal visual object classes (voc) challenge.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning The pascal visual object classes (voc) challenge

Reference 12

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This paper cites Scaling open-vocabulary image segmentation with image-level labels.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Scaling open-vocabulary image segmentation with image-level labels

Reference 13

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This paper cites Zero-shot semantic segmentation with decoupled one-pass network.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Zero-shot semantic segmentation with decoupled one-pass network

Reference 14

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This paper cites Global knowledge calibration for fast open-vocabulary segmentation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Global knowledge calibration for fast open-vocabulary segmentation

Reference 15

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This paper cites Scaling up visual and vision-language representation learning with noisy text supervision.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Scaling up visual and vision-language representation learning with noisy text supervision

Reference 16

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This paper cites Learning mask-aware clip representations for zero-shot segmentation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Learning mask-aware clip representations for zero-shot segmentation

Reference 17

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This paper cites Collaborative vision-text representation optimizing for open-vocabulary segmentation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Collaborative vision-text representation optimizing for open-vocabulary segmentation

Reference 18

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This paper cites Fineclip: Self-distilled region-based clip for better fine-grained understanding.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Fineclip: Self-distilled region-based clip for better fine-grained understanding

Reference 19

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This paper cites Language-driven semantic segmentation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Language-driven semantic segmentation

Reference 20

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This paper cites VisualBERT: A Simple and Performant Baseline for Vision and Language.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning VisualBERT: A Simple and Performant Baseline for Vision and Language

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This paper cites Open-vocabulary semantic segmentation with mask-adapted clip.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Open-vocabulary semantic segmentation with mask-adapted clip

Reference 22

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This paper cites Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C

Reference 23

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

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Remoteclip: A vision language foundation model for remote sensing

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OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Visual instruction tuning

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This paper cites Open-vocabulary segmentation with semantic-assisted calibration.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Open-vocabulary segmentation with semantic-assisted calibration

Reference 26

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This paper cites Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks

Reference 27

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This paper cites The role of context for object detection and semantic segmentation in the wild.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning The role of context for object detection and semantic segmentation in the wild

Reference 28

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This paper cites Open vocabulary semantic segmentation with patch aligned contrastive learning.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Open vocabulary semantic segmentation with patch aligned contrastive learning

Reference 29

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OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Multi-modal fusion transformer for end-to-end autonomous driving

Reference 30

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OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation

Reference 31

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This paper cites Learning transferable visual models from natural language supervision.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Learning transferable visual models from natural language supervision

Reference 32

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This paper cites Making monolingual sentence embeddings multilingual using knowledge distillation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Making monolingual sentence embeddings multilingual using knowledge distillation

Reference 33

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This paper cites LLaMA: Open and Efficient Foundation Language Models.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning LLaMA: Open and Efficient Foundation Language Models

Reference 34

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OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Hierarchical Open-vocabulary Universal Image Segmentation

Reference 35

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This paper cites Skyscript: A large and semantically diverse vision-language dataset for remote sensing.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Skyscript: A large and semantically diverse vision-language dataset for remote sensing

Reference 36

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OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Unresolved cited work

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This paper cites Towards open vocabulary learning: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(7):5092–5113, 2024.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Towards open vocabulary learning: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(7):5092–5113, 2024

Reference 38

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This paper cites Semantic projection network for zero-and few-label semantic segmentation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Semantic projection network for zero-and few-label semantic segmentation

Reference 39

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This paper cites Sed: A simple encoder-decoder for open-vocabulary semantic segmentation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Sed: A simple encoder-decoder for open-vocabulary semantic segmentation

Reference 40

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This paper cites FG-CLIP: Fine-Grained Visual and Textual Alignment.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning FG-CLIP: Fine-Grained Visual and Textual Alignment

Reference 41

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This paper cites Groupvit: Semantic segmentation emerges from text supervision.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Groupvit: Semantic segmentation emerges from text supervision

Reference 42

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This paper cites Open- vocabulary panoptic segmentation with text-to-image diffusion models.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Open- vocabulary panoptic segmentation with text-to-image diffusion models

Reference 43

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This paper cites Side adapter network for open- vocabulary semantic segmentation.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Side adapter network for open- vocabulary semantic segmentation

Reference 44

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This paper cites A simple baseline for open-vocabulary semantic segmentation with pre-trained vision-language model.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning A simple baseline for open-vocabulary semantic segmentation with pre-trained vision-language model

Reference 45

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This paper cites Qwen2.5 Technical Report.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Qwen2.5 Technical Report

Reference 46

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This paper cites Griffiths, Yuan Cao, and Karthik Narasimhan.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Griffiths, Yuan Cao, and Karthik Narasimhan

Reference 47

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This paper cites Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP

Reference 48

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OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Unresolved cited work

Reference 49

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This paper cites Open vocabulary scene parsing.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Open vocabulary scene parsing

Reference 50

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This paper cites A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities

Reference 51

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This paper cites Semantic understanding of scenes through the ade20k dataset.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Semantic understanding of scenes through the ade20k dataset

Reference 52

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Observation c2b565aa-38f2-4291-94d4-e5c6c474e51e · outbound

This paper cites Extract free dense labels from clip.

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning Extract free dense labels from clip

Reference 53

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