Zhou et al., 2021 - Google Patents
TMFNet: Three-input multilevel fusion network for detecting salient objects in RGB-D imagesZhou et al., 2021
- Document ID
- 8054296241278059451
- Author
- Zhou W
- Pan S
- Lei J
- Yu L
- Publication year
- Publication venue
- IEEE Transactions on Emerging Topics in Computational Intelligence
External Links
Snippet
The use of depth information, acquired by depth sensors, for salient object detection (SOD) is being explored. Despite the remarkable results from recent deep learning approaches for RGB-D SOD, they fail to fully incorporate original and accurate information to express details …
- 230000004927 fusion 0 title abstract description 35
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30781—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F17/30784—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre
- G06F17/30799—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre using low-level visual features of the video content
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
- G06K9/00268—Feature extraction; Face representation
- G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/20—Image acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Zhou et al. | ECFFNet: Effective and consistent feature fusion network for RGB-T salient object detection | |
Zhou et al. | IRFR-Net: Interactive recursive feature-reshaping network for detecting salient objects in RGB-D images | |
Zhou et al. | TMFNet: Three-input multilevel fusion network for detecting salient objects in RGB-D images | |
Huo et al. | Efficient context-guided stacked refinement network for RGB-T salient object detection | |
Wang et al. | Adaptive fusion for RGB-D salient object detection | |
Zhai et al. | Bifurcated backbone strategy for RGB-D salient object detection | |
Li et al. | Cross-layer feature pyramid network for salient object detection | |
Fu et al. | Siamese network for RGB-D salient object detection and beyond | |
Zhou et al. | CCAFNet: Crossflow and cross-scale adaptive fusion network for detecting salient objects in RGB-D images | |
Li et al. | ASIF-Net: Attention steered interweave fusion network for RGB-D salient object detection | |
Piao et al. | Depth-induced multi-scale recurrent attention network for saliency detection | |
Chen et al. | Spatial-temporal attention-aware learning for video-based person re-identification | |
Liu et al. | Deep salient object detection with contextual information guidance | |
Yang et al. | Bi-directional progressive guidance network for RGB-D salient object detection | |
Wu et al. | Multiscale multilevel context and multimodal fusion for RGB-D salient object detection | |
Chen et al. | CGMDRNet: Cross-guided modality difference reduction network for RGB-T salient object detection | |
Sun et al. | CATNet: A cascaded and aggregated transformer network for RGB-D salient object detection | |
Zhao et al. | RGB-D salient object detection with ubiquitous target awareness | |
Xu et al. | Video salient object detection via robust seeds extraction and multi-graphs manifold propagation | |
Chen et al. | Multiframe-to-multiframe network for video denoising | |
Chen et al. | Confidence-guided adaptive gate and dual differential enhancement for video salient object detection | |
Liu et al. | Deep layer guided network for salient object detection | |
Niu et al. | Boundary-aware RGBD salient object detection with cross-modal feature sampling | |
Bai et al. | Circular complement network for RGB-D salient object detection | |
Liu et al. | Asymmetric deeply fused network for detecting salient objects in RGB-D images |