Camouflaged Object Segmentation
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Benchmarks
PCOD_1200
CAMO
COD
CHAMELEON
NC4K
MoCA-Mask
Camouflaged Animal Dataset
Most implemented
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
EGNet: Edge Guidance Network for Salient Object Detection
Boundary-Aware Segmentation Network for Mobile and Web Applications
PraNet: Parallel Reverse Attention Network for Polyp Segmentation
F3Net: Fusion, Feedback and Focus for Salient Object Detection
BASNet: Boundary-Aware Salient Object Detection
Papers
Discover, Segment, and Select: A Progressive Mechanism for Zero-shot Camouflaged Object Segmentation
Current zero-shot Camouflaged Object Segmentation methods typically employ a two-stage pipeline (discover-then-segment): using MLLMs to obtain visual prompts, followed by SAM segmentation. However, relying solely on MLLM…
Camouflaged Object SegmentationContext-measure: Contextualizing Metric for Camouflage
Camouflage relies heavily on context, but current metrics used in camouflaged object segmentation ignore contextual cues. We identify two major drawbacks of these metrics: first, the Dimension Flaw - a predicted foregrou…
Camouflaged Object SegmentationClassifier-Centric Adaptive Framework for Open-Vocabulary Camouflaged Object Segmentation
Open-vocabulary camouflaged object segmentation requires models to segment camouflaged objects of arbitrary categories unseen during training, placing extremely high demands on generalization capabilities. Through analys…
Camouflaged Object SegmentationArgusCogito: Chain-of-Thought for Cross-Modal Synergy and Omnidirectional Reasoning in Camouflaged Object Segmentation
Camouflaged Object Segmentation (COS) poses a significant challenge due to the intrinsic high similarity between targets and backgrounds, demanding models capable of profound holistic understanding beyond superficial cue…
Camouflaged Object SegmentationMedical Image SegmentationScene UnderstandingAn Instance-Aware Prompting Framework for Training-free Camouflaged Object Segmentation
Training-free Camouflaged Object Segmentation (COS) seeks to segment camouflaged objects without task-specific training, by automatically generating visual prompts to guide the Segment Anything Model (SAM). However, exis…
Camouflaged Object SegmentationDC-TTA: Divide-and-Conquer Framework for Test-Time Adaptation of Interactive Segmentation
Interactive segmentation (IS) allows users to iteratively refine object boundaries with minimal cues, such as positive and negative clicks. While the Segment Anything Model (SAM) has garnered attention in the IS communit…
Camouflaged Object SegmentationInteractive SegmentationSegmentationSemantic Segmentation+1