# Boosting Camouflaged Object Detection with Dual-Task Interactive Transformer

arXiv: https://arxiv.org/abs/2205.10579 · HTML: https://mlsanity.com/paper/2205.10579/

## Key facts

- Cited by 24 papers in the map (data through 14 Oct 2026).
- Builds on 25 of its 49 references that are in the map.
- First posted on arXiv 21 May 2022.

## Builds on (most cited first, 25 of 25)

- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021)
- [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://mlsanity.com/paper/2105.15203/) (2021)
- [Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions](https://mlsanity.com/paper/2102.12122/) (2021)
- [Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet](https://mlsanity.com/paper/2101.11986/) (2021)
- [CvT: Introducing Convolutions to Vision Transformers](https://mlsanity.com/paper/2103.15808/) (2021)
- [PVT v2: Improved Baselines with Pyramid Vision Transformer](https://mlsanity.com/paper/2106.13797/) (2021)
- [Twins: Revisiting the Design of Spatial Attention in Vision Transformers](https://mlsanity.com/paper/2104.13840/) (2021)
- [EGNet:Edge Guidance Network for Salient Object Detection](https://mlsanity.com/paper/1908.08297/) (2019)
- [Anabranch Network for Camouflaged Object Segmentation](https://mlsanity.com/paper/2105.09451/) (2021)
- [Concealed Object Detection](https://mlsanity.com/paper/2102.10274/) (2021)
- [Simultaneously Localize, Segment and Rank the Camouflaged Objects](https://mlsanity.com/paper/2103.04011/) (2021)
- [Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT Images](https://mlsanity.com/paper/2004.14133/) (2020)
- [F3Net: Fusion, Feedback and Focus for Salient Object Detection](https://mlsanity.com/paper/1911.11445/) (2019)
- [Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers](https://mlsanity.com/paper/2108.06932/) (2021)
- [Camouflaged Object Segmentation with Distraction Mining](https://mlsanity.com/paper/2104.10475/) (2021)
- [Uncertainty-aware Joint Salient Object and Camouflaged Object Detection](https://mlsanity.com/paper/2104.02628/) (2021)
- [Mutual Graph Learning for Camouflaged Object Detection](https://mlsanity.com/paper/2104.02613/) (2021)
- [Context-aware Cross-level Fusion Network for Camouflaged Object Detection](https://mlsanity.com/paper/2105.12555/) (2021)
- [UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation](https://mlsanity.com/paper/2107.02368/) (2021)
- [Boundary-Aware Segmentation Network for Mobile and Web Applications](https://mlsanity.com/paper/2101.04704/) (2021)
- [Fast Camouflaged Object Detection via Edge-based Reversible Re-calibration Network](https://mlsanity.com/paper/2111.03216/) (2021)
- [Deep Texture-Aware Features for Camouflaged Object Detection](https://mlsanity.com/paper/2102.02996/) (2021)
- [A Fusion Framework for Camouflaged Moving Foreground Detection in the Wavelet Domain](https://mlsanity.com/paper/1804.05984/) (2018)
- [Confidence-Aware Learning for Camouflaged Object Detection](https://mlsanity.com/paper/2106.11641/) (2021)

## Built on by (most cited first, 24 of 24)

- [Feature Shrinkage Pyramid for Camouflaged Object Detection with Transformers](https://mlsanity.com/paper/2303.14816/) (2023)
- [CamoFormer: Masked Separable Attention for Camouflaged Object Detection](https://mlsanity.com/paper/2212.06570/) (2022)
- [Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects](https://mlsanity.com/paper/2308.03166/) (2023)
- [Advances in Deep Concealed Scene Understanding](https://mlsanity.com/paper/2304.11234/) (2023)
- [CamoDiffusion: Camouflaged Object Detection via Conditional Diffusion Models](https://mlsanity.com/paper/2305.17932/) (2023)
- [Hierarchical Graph Interaction Transformer with Dynamic Token Clustering for Camouflaged Object Detection](https://mlsanity.com/paper/2408.15020/) (2024)
- [FocusDiffuser: Perceiving Local Disparities for Camouflaged Object Detection](https://mlsanity.com/paper/2407.13133/) (2024)
- [CamoTeacher: Dual-Rotation Consistency Learning for Semi-Supervised Camouflaged Object Detection](https://mlsanity.com/paper/2408.08050/) (2024)
- [Large Model Based Referring Camouflaged Object Detection](https://mlsanity.com/paper/2311.17122/) (2023)
- [Towards Complex Backgrounds: A Unified Difference-Aware Decoder for Binary Segmentation](https://mlsanity.com/paper/2210.15156/) (2022)
- [PlantCamo: Plant Camouflage Detection](https://mlsanity.com/paper/2410.17598/) (2024)
- [Mamba Capsule Routing Towards Part-Whole Relational Camouflaged Object Detection](https://mlsanity.com/paper/2410.03987/) (2024)
- [Cross-level Attention with Overlapped Windows for Camouflaged Object Detection](https://mlsanity.com/paper/2311.16618/) (2023)
- [C3Net: Context-Contrast Network for Camouflaged Object Detection](https://mlsanity.com/paper/2511.12627/) (2025)
- [Assisted Refinement Network Based on Channel Information Interaction for Camouflaged and Salient Object Detection](https://mlsanity.com/paper/2512.11369/) (2025)
- [Boundary-aware Camouflaged Object Detection via Deformable Point Sampling](https://mlsanity.com/paper/2211.12048/) (2022)
- [B-GRTO: Bootstrapped Group Relative Tool Optimization for Referring Segmentation](https://mlsanity.com/paper/2605.23500/) (2026)
- [Weakly Supervised Camouflaged Object Detection Based on the SAM Model and Mask Guidance](https://mlsanity.com/paper/2605.25385/) (2026)
- [A bioinspired three-stage model for camouflaged object detection](https://mlsanity.com/paper/2305.12635/) (2023)
- [A Revisit to the Decoder for Camouflaged Object Detection](https://mlsanity.com/paper/2503.14035/) (2025)
- [First RAG, Second SEG: A Training-Free Paradigm for Camouflaged Object Detection](https://mlsanity.com/paper/2508.15313/) (2025)
- [SPEGNet: Synergistic Perception-Guided Network for Camouflaged Object Detection](https://mlsanity.com/paper/2510.04472/) (2025)
- [MSRNet: A Multi-Scale Recursive Network for Camouflaged Object Detection](https://mlsanity.com/paper/2511.12810/) (2025)
- [CamoNAS: Neural Architecture Search for Enhanced Camouflaged Object Detection](https://mlsanity.com/paper/2607.01870/) (2026)

## Abstract (arXiv)

Camouflaged object detection intends to discover the concealed objects hidden in the surroundings. Existing methods follow the bio-inspired framework, which first locates the object and second refines the boundary. We argue that the discovery of camouflaged objects depends on the recurrent search for the object and the boundary. The recurrent processing makes the human tired and helpless, but it is just the advantage of the transformer with global search ability. Therefore, a dual-task interactive transformer is proposed to detect both accurate position of the camouflaged object and its detailed boundary. The boundary feature is considered as Query to improve the camouflaged object detection, and meanwhile the object feature is considered as Query to improve the boundary detection. The camouflaged object detection and the boundary detection are fully interacted by multi-head self-attention. Besides, to obtain the initial object feature and boundary feature, transformer-based backbones are adopted to extract the foreground and background. The foreground is just object, while foreground minus background is considered as boundary. Here, the boundary feature can be obtained from blurry boundary region of the foreground and background. Supervised by the object, the background and the boundary ground truth, the proposed model achieves state-of-the-art performance in public datasets. https://github.com/liuzywen/COD