Camouflaged Object Segmentation

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

7 leaderboard tables shown for this task, 7 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

7 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 38 papers with code (47 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• UNet++: A Nested U-Net Architecture for Medical Image Segmentation
  18 Jul 2018 34 repositories listed Syntology ran 5 of 28 samples · 23 unverified · 2 pointer-only (licence)
  Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet
• EGNet: Edge Guidance Network for Salient Object Detection
  1 Oct 2019 7 repositories listed
  In the second step, we integrate the local edge information and global location information to obtain the salient edge features.
• Boundary-Aware Segmentation Network for Mobile and Web Applications
  12 Jan 2021 5 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  In this paper, we propose a simple yet powerful Boundary-Aware Segmentation Network (BASNet), which comprises a predict-refine architecture and a hybrid loss, for highly accurate image segmentation.
• PraNet: Parallel Reverse Attention Network for Polyp Segmentation
  13 Jun 2020 4 repositories listed Syntology ran 0 of 9 samples · 9 unverified
  To address these challenges, we propose a parallel reverse attention network (PraNet) for accurate polyp segmentation in colonoscopy images.
• F3Net: Fusion, Feedback and Focus for Salient Object Detection
  26 Nov 2019 4 repositories listed
  Furthermore, different from binary cross entropy, the proposed PPA loss doesn't treat pixels equally, which can synthesize the local structure information of a pixel to guide the network to focus more on local details.
• BASNet: Boundary-Aware Salient Object Detection
  1 Jun 2019 3 repositories listed
  In this paper, we propose a predict-refine architecture, BASNet, and a new hybrid loss for Boundary-Aware Salient object detection.
• Integrating Extra Modality Helps Segmentor Find Camouflaged Objects Well
  20 Feb 2025 2 repositories listed
  Camouflaged Object Segmentation (COS) remains challenging because camouflaged objects exhibit only subtle visual differences from their backgrounds and single-modality RGB methods provide limited cues, leading…
• Explicit Visual Prompting for Universal Foreground Segmentations
  29 May 2023 2 repositories listed
  We take inspiration from the widely-used pre-training and then prompt tuning protocols in NLP and propose a new visual prompting model, named Explicit Visual Prompting (EVP).
• Camouflaged Object Detection via Context-aware Cross-level Fusion
  27 Jul 2022 2 repositories listed Syntology ran 2 of 7 samples · 5 unverified
  To address these challenges, we propose a novel Context-aware Cross-level Fusion Network (C2F-Net), which fuses context-aware cross-level features for accurately identifying camouflaged objects.
• Context-aware Cross-level Fusion Network for Camouflaged Object Detection
  26 May 2021 2 repositories listed Syntology ran 7 of 9 samples · 2 unverified
  Camouflaged object detection (COD) is a challenging task due to the low boundary contrast between the object and its surroundings.
• Anabranch Network for Camouflaged Object Segmentation
  20 May 2021 2 repositories listed
  Different from existing networks for segmentation, our proposed network possesses the second branch for classification to predict the probability of containing camouflaged object(s) in an image, which is then fused into…
• Generative Transformer for Accurate and Reliable Salient Object Detection
  20 Apr 2021 2 repositories listed
  For the former, we apply transformer to a deterministic model, and explain that the effective structure modeling and global context modeling abilities lead to its superior performance compared with the CNN based…
• Camouflaged Object Detection
  1 Jun 2020 2 repositories listed
  We present a comprehensive study on a new task named camouflaged object detection (COD), which aims to identify objects that are "seamlessly" embedded in their surroundings.
• Open-Vocabulary Camouflaged Object Segmentation with Cascaded Vision Language Models
  24 Jun 2025 1 repository listed
  Open-Vocabulary Camouflaged Object Segmentation (OVCOS) seeks to segment and classify camouflaged objects from arbitrary categories, presenting unique challenges due to visual ambiguity and unseen categories.
• Stepwise Decomposition and Dual-stream Focus: A Novel Approach for Training-free Camouflaged Object Segmentation
  7 Jun 2025 1 repository listed
  MSD-CoT progressively disentangles image captions to eliminate semantic ambiguity, while RDVP injects spatial constraints into visual prompting and independently samples visual prompts for foreground and background…
• ZS-VCOS: Zero-Shot Outperforms Supervised Video Camouflaged Object Segmentation
  10 Apr 2025 1 repository listed
  Our method integrates optical flow, a vision-language model, and SAM 2 into a sequential pipeline.
• ZS-VCOS: Zero-Shot Outperforms Supervised Video Camouflaged Object Segmentation with Zero-Shot Method
  30 Mar 2025 1 repository listed
  Our method integrates optical flow, a vision-language model, and SAM 2 into a sequential pipeline, where the output of one component provides cues for the next.
• CamSAM2: Segment Anything Accurately in Camouflaged Videos
  25 Mar 2025 1 repository listed
  Video camouflaged object segmentation (VCOS), aiming at segmenting camouflaged objects that seamlessly blend into their environment, is a fundamental vision task with various real-world applications.
• FOCUS: Towards Universal Foreground Segmentation
  9 Jan 2025 1 repository listed
  Foreground segmentation is a fundamental task in computer vision, encompassing various subdivision tasks.
• When SAM2 Meets Video Camouflaged Object Segmentation: A Comprehensive Evaluation and Adaptation
  27 Sep 2024 1 repository listed
  This study presents a comprehensive study on SAM2's ability in VCOS.
• Leveraging Hallucinations to Reduce Manual Prompt Dependency in Promptable Segmentation
  27 Aug 2024 1 repository listed Syntology ran 2 of 9 samples · 7 unverified
  In this paper, we utilize hallucinations to mine task-related information from images and verify its accuracy for enhancing precision of the generated prompts.
• Unlocking Attributes' Contribution to Successful Camouflage: A Combined Textual and VisualAnalysis Strategy
  22 Aug 2024 1 repository listed
  In the domain of Camouflaged Object Segmentation (COS), despite continuous improvements in segmentation performance, the underlying mechanisms of effective camouflage remain poorly understood, akin to a black box.
• Bilateral Reference for High-Resolution Dichotomous Image Segmentation
  7 Jan 2024 1 repository listed Syntology ran 13 of 14 samples · 1 unverified
  It comprises two essential components: the localization module (LM) and the reconstruction module (RM) with our proposed bilateral reference (BiRef).
• Open-Vocabulary Camouflaged Object Segmentation
  19 Nov 2023 1 repository listed
  With the proposed dataset and baseline, we hope that this new task with more practical value can further expand the research on open-vocabulary dense prediction tasks.
• ZoomNeXt: A Unified Collaborative Pyramid Network for Camouflaged Object Detection
  31 Oct 2023 1 repository listed Syntology ran 8 of 11 samples · 3 unverified · 11 pointer-only (licence)
  Apart from the high intrinsic similarity between camouflaged objects and their background, objects are usually diverse in scale, fuzzy in appearance, and even severely occluded.
• Unsupervised Camouflaged Object Segmentation as Domain Adaptation
  8 Aug 2023 1 repository listed
  To this end, we formulate the UCOS as a source-free unsupervised domain adaptation task (UCOS-DA), where both source labels and target labels are absent during the whole model training process.
• Improving existing segmentators performance with zero-shot segmentators
  26 Jul 2023 1 repository listed
  We release with this paper the open-source implementation of our method.
• Edge-Aware Mirror Network for Camouflaged Object Detection
  8 Jul 2023 1 repository listed
  Existing edge-aware camouflaged object detection (COD) methods normally output the edge prediction in the early stage.
• The Art of Camouflage: Few-Shot Learning for Animal Detection and Segmentation
  15 Apr 2023 1 repository listed
  Camouflaged object detection and segmentation is a new and challenging research topic in computer vision.
• Explicit Visual Prompting for Low-Level Structure Segmentations
  20 Mar 2023 1 repository listed Syntology ran 4 of 4 samples · 0 unverified
  Different from the previous visual prompting which is typically a dataset-level implicit embedding, our key insight is to enforce the tunable parameters focusing on the explicit visual content from each individual…

Syntology lines on 9 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.