mlsanityData to 7 Oct 2026

Chain of Visual Perception: Harnessing Multimodal Large Language Models for Zero-shot Camouflaged Object Detection

arXiv 2311.11273 ↗First posted 19 Nov 2023cs.CVcited by 22

On the map: Multimodal LLMs / vision-language models → Driving VLMs and open-vocabulary detection

Abstract (arXiv)

In this paper, we introduce a novel multimodal camo-perceptive framework (MMCPF) aimed at handling zero-shot Camouflaged Object Detection (COD) by leveraging the powerful capabilities of Multimodal Large Language Models (MLLMs). Recognizing the inherent limitations of current COD methodologies, which predominantly rely on supervised learning models demanding extensive and accurately annotated datasets, resulting in weak generalization, our research proposes a zero-shot MMCPF that circumvents these challenges. Although MLLMs hold significant potential for broad applications, their effectiveness in COD is hindered and they would make misinterpretations of camouflaged objects. To address this challenge, we further propose a strategic enhancement called the Chain of Visual Perception (CoVP), which significantly improves the perceptual capabilities of MLLMs in camouflaged scenes by leveraging both linguistic and visual cues more effectively. We validate the effectiveness of MMCPF on five widely used COD datasets, containing CAMO, COD10K, NC4K, MoCA-Mask and OVCamo. Experiments show that MMCPF can outperform all existing state-of-the-art zero-shot COD methods, and achieve competitive performance compared to weakly-supervised and fully-supervised methods, which demonstrates the potential of MMCPF. The Github link of this paper is urlhttps://github.com/luckybird1994/MMCPF.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Placed in Driving VLMs and open-vocabulary detection, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 28 of its 50 references that are in the map. First posted on arXiv 19 Nov 2023.

Builds on

28 of 50 references.

References · 28

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  3. 2020Language Models are Few-Shot Learnerscited by 32,199
  4. 2022Large Language Models are Zero-Shot Reasonerscited by 4,323
  5. 2023InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuningcited by 2,855
  6. 2019ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Taskscited by 2,219
  7. 2023Kosmos-2: Grounding Multimodal Large Language Models to the Worldcited by 1,075
  8. 2023Shikra: Unleashing Multimodal LLM's Referential Dialogue Magiccited by 891
  9. 2023LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attentioncited by 776
  10. 2017Structure-measure: A New Way to Evaluate Foreground Mapscited by 480
  11. 2022Complexity-Based Prompting for Multi-Step Reasoningcited by 387
  12. 2023Segment Anything in High Qualitycited by 373
16 more
  1. 2023GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interestcited by 300
  2. 2023Personalize Segment Anything Model with One Shotcited by 250
  3. 2021Anabranch Network for Camouflaged Object Segmentationcited by 227
  4. 2021Self-supervised Video Object Segmentation by Motion Groupingcited by 147
  5. 2023Matcher: Segment Anything with One Shot Using All-Purpose Feature Matchingcited by 142
  6. 2021Salient Object Detection via Integrity Learningcited by 133
  7. 2023DetGPT: Detect What You Need via Reasoningcited by 112
  8. 2021Mutual Graph Learning for Camouflaged Object Detectioncited by 103
  9. 2023Feature Shrinkage Pyramid for Camouflaged Object Detection with Transformerscited by 87
  10. 2022Deep Gradient Learning for Efficient Camouflaged Object Detectioncited by 65
  11. 2023ChatSpot: Bootstrapping Multimodal LLMs via Precise Referring Instruction Tuningcited by 65
  12. 2022Weakly-Supervised Camouflaged Object Detection with Scribble Annotationscited by 43
  13. 2021Warp Consistency for Unsupervised Learning of Dense Correspondencescited by 42
  14. 2021Fast Camouflaged Object Detection via Edge-based Reversible Re-calibration Networkcited by 42
  15. 2023Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Leadcited by 40
  16. 2020Camouflaged Object Detection and Tracking: A Surveycited by 13

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 5; 2025: 13; 2026: 4.

22 papers.

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  1. 2024A Survey of Camouflaged Object Detection and Beyondcited by 37
  2. 2025SAM-R1: Leveraging SAM for Reward Feedback in Multimodal Segmentation via Reinforcement Learningcited by 31
  3. 2024Evaluating and Analyzing Relationship Hallucinations in Large Vision-Language Modelscited by 27
  4. 2025Object Detection with Multimodal Large Vision-Language Models: An In-depth Reviewcited by 14
  5. 2024Evaluating SAM2's Role in Camouflaged Object Detection: From SAM to SAM2cited by 12
  6. 2024When SAM2 Meets Video Camouflaged Object Segmentation: A Comprehensive Evaluation and Adaptationcited by 11
  7. 2025Deep Learning in Concealed Dense Predictioncited by 6
  8. 2025Beyond Single Images: Retrieval Self-Augmented Unsupervised Camouflaged Object Detectioncited by 5
  9. 2026Grounding the Score: Explicit Visual Premise Verification for Reliable Vision-Language Process Reward Modelscited by 4
  10. 2024Towards Real Zero-Shot Camouflaged Object Segmentation without Camouflaged Annotationscited by 3
  11. 2025LLM-EvRep: Learning an LLM-Compatible Event Representation Using a Self-Supervised Frameworkcited by 3
  12. 2025Align and Surpass Human Camouflaged Perception: Visual Refocus Reinforcement Fine-Tuningcited by 3
10 more
  1. 2025Stepwise Decomposition and Dual-stream Focus: A Novel Approach for Training-free Camouflaged Object Segmentationcited by 3
  2. 2026Discover, Segment, and Select: A Progressive Mechanism for Zero-shot Camouflaged Object Segmentationcited by 3
  3. 2025Marine Saliency Segmenter: Object-Focused Conditional Diffusion with Region-Level Semantic Knowledge Distillationcited by 2
  4. 2025ZS-VCOS: Zero-Shot Video Camouflaged Object Segmentation By Optical Flow and Open Vocabulary Object Detectioncited by 2
  5. 2025SAEC: Scene-Aware Enhanced Edge-Cloud Collaborative Industrial Vision Inspection with Multimodal LLMcited by 2
  6. 2025AutoMiSeg: Automatic Medical Image Segmentation via Test-Time Adaptation of Foundation Modelscited by 0
  7. 2025Phantom-Insight: Adaptive Multi-cue Fusion for Video Camouflaged Object Detection with Multimodal LLMcited by 0
  8. 2025Classifier-Centric Adaptive Framework for Open-Vocabulary Camouflaged Object Segmentationcited by 0
  9. 2026Camouflage-aware Image-Text Retrieval via Expert Collaborationcited by 0
  10. 2026AgroTools: A Benchmark for Tool-Augmented Multimodal Agents in Agriculturecited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026LAD-COD: Language-Aligned Dense Perception for Camouflaged Object Detection
  2. 2023Large Model Based Referring Camouflaged Object Detection
  3. 2024MM-CamObj: A Comprehensive Multimodal Dataset for Camouflaged Object Scenarios
  4. 2023CamDiff: Camouflage Image Augmentation via Diffusion Model
  5. 2025Roboflow100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language Models
  6. 2023Revisiting Few-Shot Object Detection with Vision-Language Models
  7. 2025ArgusCogito: Chain-of-Thought for Cross-Modal Synergy and Omnidirectional Reasoning in Camouflaged Object Segmentation
  8. 2025First RAG, Second SEG: A Training-Free Paradigm for Camouflaged Object Detection