Co-Salient Object Detection
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Benchmarks
Most implemented
EGNet: Edge Guidance Network for Salient Object Detection
GCoNet+: A Stronger Group Collaborative Co-Salient Object Detector
Memory-aided Contrastive Consensus Learning for Co-salient Object Detection
Global-and-Local Collaborative Learning for Co-Salient Object Detection
Re-thinking Co-Salient Object Detection
Visual Consensus Prompting for Co-Salient Object Detection
Papers
TF-SSD: A Strong Pipeline via Synergic Mask Filter for Training-free Co-salient Object Detection
Co-salient Object Detection (CoSOD) aims to segment salient objects that consistently appear across a group of related images. Despite the notable progress achieved by recent training-based approaches, they still remain …
Co-Salient Object DetectionSaliency-R1: Incentivizing Unified Saliency Reasoning Capability in MLLM with Confidence-Guided Reinforcement Learning
Although multimodal large language models (MLLMs) excel in high-level vision-language reasoning, they lack inherent awareness of visual saliency, making it difficult to identify key visual elements. To bridge this gap, w…
Co-Salient Object DetectionReinforcement LearningInstance SegmentationVisual Consensus Prompting for Co-Salient Object Detection
Existing co-salient object detection (CoSOD) methods generally employ a three-stage architecture (i.e., encoding, consensus extraction & dispersion, and prediction) along with a typical full fine-tuning paradigm. Althoug…
Co-Salient Object Detectionobject-detectionObject DetectionSalient Object DetectionCONDA: Condensed Deep Association Learning for Co-Salient Object Detection
Inter-image association modeling is crucial for co-salient object detection. Despite satisfactory performance, previous methods still have limitations on sufficient inter-image association modeling. Because most of them …
Co-Salient Object Detectionobject-detectionObject DetectionSalient Object Detection+1CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection
Co-salient object detection (CoSOD) aims to identify the common and salient (usually in the foreground) regions across a given group of images. Although achieving significant progress, state-of-the-art CoSODs could be ea…
Adversarial AttackCo-Salient Object Detectionobject-detectionObject Detection+2Self-supervised co-salient object detection via feature correspondence at multiple scales
Our paper introduces a novel two-stage self-supervised approach for detecting co-occurring salient objects (CoSOD) in image groups without requiring segmentation annotations. Unlike existing unsupervised methods that rel…
Co-Salient Object Detectionobject-detectionObject DetectionSalient Object Detection