Review of Visual Saliency Detection with Comprehensive Information
arXiv:1803.03391 · doi:10.1109/TCSVT.2018.2870832
Abstract
Visual saliency detection model simulates the human visual system to perceive the scene, and has been widely used in many vision tasks. With the acquisition technology development, more comprehensive information, such as depth cue, inter-image correspondence, or temporal relationship, is available to extend image saliency detection to RGBD saliency detection, co-saliency detection, or video saliency detection. RGBD saliency detection model focuses on extracting the salient regions from RGBD images by combining the depth information. Co-saliency detection model introduces the inter-image correspondence constraint to discover the common salient object in an image group. The goal of video saliency detection model is to locate the motion-related salient object in video sequences, which considers the motion cue and spatiotemporal constraint jointly. In this paper, we review different types of saliency detection algorithms, summarize the important issues of the existing methods, and discuss the existent problems and future works. Moreover, the evaluation datasets and quantitative measurements are briefly introduced, and the experimental analysis and discission are conducted to provide a holistic overview of different saliency detection methods.
18 pages, 11 figures, 7 tables, Accepted by IEEE Transactions on Circuits and Systems for Video Technology 2018, https://rmcong.github.io/
References in corpus (1)
Cited by in corpus (52)
- Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks
- SwinNet: Swin Transformer drives edge-aware RGB-D and RGB-T salient object detection
- Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images
- RGB-D Salient Object Detection: A Survey
- DPANet: Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object Detection
- CIR-Net: Cross-modality Interaction and Refinement for RGB-D Salient Object Detection
- Bilateral Attention Network for RGB-D Salient Object Detection
- HiDAnet: RGB-D Salient Object Detection via Hierarchical Depth Awareness
- HRTransNet: HRFormer-Driven Two-Modality Salient Object Detection
- Re-thinking Co-Salient Object Detection
- Lightweight Salient Object Detection in Optical Remote Sensing Images via Feature Correlation
- Lightweight Salient Object Detection in Optical Remote-Sensing Images via Semantic Matching and Edge Alignment
- Salient Object Detection in Optical Remote Sensing Images Driven by Transformer
- Multi-Content Complementation Network for Salient Object Detection in Optical Remote Sensing Images
- Review: Deep Learning in Electron Microscopy
- A Parallel Down-Up Fusion Network for Salient Object Detection in Optical Remote Sensing Images
- SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization
- SCGAN: Saliency Map-guided Colorization with Generative Adversarial Network
- Salient Objects in Clutter
- Salient Object Detection in Video using Deep Non-Local Neural Networks
- Open World Object Detection: A Survey
- Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB Images
- Towards Stable Co-saliency Detection and Object Co-segmentation
- DNA: Deeply-supervised Nonlinear Aggregation for Salient Object Detection
- Online Visual Place Recognition via Saliency Re-identification
- ViDSOD-100: A New Dataset and a Baseline Model for RGB-D Video Salient Object Detection
- Human-Perception-Oriented Pseudo Analog Video Transmissions with Deep Learning
- Center Emphasized Visual Saliency and a Contrast-based Full Reference Image Quality Index
- Global Context-Aware Progressive Aggregation Network for Salient Object Detection
- CoSformer: Detecting Co-Salient Object with Transformers
- Spatio-Temporal Perturbations for Video Attribution
- A Psychophysically Oriented Saliency Map Prediction Model
- RGB-D Salient Object Detection with Cross-Modality Modulation and Selection
- An End-to-End Network for Co-Saliency Detection in One Single Image
- Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection
- Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection
- XRAI: Better Attributions Through Regions
- Cross-modality Discrepant Interaction Network for RGB-D Salient Object Detection
- Salient Object Detection via High-to-Low Hierarchical Context Aggregation
- HSCS: Hierarchical Sparsity Based Co-saliency Detection for RGBD Images
- RRNet: Relational Reasoning Network with Parallel Multi-scale Attention for Salient Object Detection in Optical Remote Sensing Images
- BridgeNet: A Joint Learning Network of Depth Map Super-Resolution and Monocular Depth Estimation
- Progressive Self-Guided Loss for Salient Object Detection
- Triple-cooperative Video Shadow Detection
- A Novel Video Salient Object Detection Method via Semi-supervised Motion Quality Perception
- A Unified Structure for Efficient RGB and RGB-D Salient Object Detection
- Leveraging Local Structure for Improving Model Explanations: An Information Propagation Approach
- Dual Domain-Adversarial Learning for Audio-Visual Saliency Prediction
- Image Co-skeletonization via Co-segmentation
- Co-Saliency Detection with Co-Attention Fully Convolutional Network
- Superpixel Segmentation Based on Spatially Constrained Subspace Clustering
- Using Saliency and Cropping to Improve Video Memorability