Papers with Code 아카이브
RGB Salient Object Detection
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RGB Salient object detection is a task-based on a visual attention mechanism, in which algorithms aim to explore objects or regions more attentive than the surrounding areas on the scene or RGB images.
<span style="color:grey; opacity: 0.6">( Image credit: Attentive Feedback Network for Boundary-Aware Salient Object Detection )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Saliency-Motion Guided Trunk-Collateral Network for Unsupervised Video Object Segmentation
Patch-Depth Fusion: Dichotomous Image Segmentation via Fine-Grained Patch Strategy and Depth Integrity-Prior
Learning Motion and Temporal Cues for Unsupervised Video Object Segmentation
CPDR: Towards Highly-Efficient Salient Object Detection via Crossed Post-decoder Refinement
BEN: Using Confidence-Guided Matting for Dichotomous Image Segmentation
Mask Factory: Towards High-quality Synthetic Data Generation for Dichotomous Image Segmentation
Transforming Static Images Using Generative Models for Video Salient Object Detection
High-Precision Dichotomous Image Segmentation via Probing Diffusion Capacity
Evaluation Study on SAM 2 for Class-agnostic Instance-level Segmentation
CONDA: Condensed Deep Association Learning for Co-Salient Object Detection
Improving Unsupervised Video Object Segmentation via Fake Flow Generation
CoLA: Conditional Dropout and Language-driven Robust Dual-modal Salient Object Detection
ViDSOD-100: A New Dataset and a Baseline Model for RGB-D Video Salient Object Detection
Multi-view Aggregation Network for Dichotomous Image Segmentation
CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection
Self-supervised co-salient object detection via feature correspondence at multiple scales
Reframe Anything: LLM Agent for Open World Video Reframing
Discriminative Consensus Mining with A Thousand Groups for More Accurate Co-Salient Object Detection
Bilateral Reference for High-Resolution Dichotomous Image Segmentation
Promoting Segment Anything Model towards Highly Accurate Dichotomous Image Segmentation
SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process
SimulFlow: Simultaneously Extracting Feature and Identifying Target for Unsupervised Video Object Segmentation
Unsupervised and semi-supervised co-salient object detection via segmentation frequency statistics
Towards Open-World Co-Salient Object Detection with Generative Uncertainty-aware Group Selective Exchange-Masking
A Spatial-Temporal Dual-Mode Mixed Flow Network for Panoramic Video Salient Object Detection
UniST: Towards Unifying Saliency Transformer for Video Saliency Prediction and Detection
M$^3$Net: Multilevel, Mixed and Multistage Attention Network for Salient Object Detection
Co-Salient Object Detection with Semantic-Level Consensus Extraction and Dispersion
Zero-Shot Co-salient Object Detection Framework
Unite-Divide-Unite: Joint Boosting Trunk and Structure for High-accuracy Dichotomous Image Segmentation
Advancing Referring Expression Segmentation Beyond Single Image
SegGPT Meets Co-Saliency Scene
Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detection
Co-Salient Object Detection with Co-Representation Purification
Memory-aided Contrastive Consensus Learning for Co-salient Object Detection
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