Nothing Special   »   [go: up one dir, main page]

Jing et al., 2021 - Google Patents

Occlusion-aware bi-directional guided network for light field salient object detection

Jing et al., 2021

Document ID
961513696755190021
Author
Jing D
Zhang S
Cong R
Lin Y
Publication year
Publication venue
Proceedings of the 29th ACM International Conference on Multimedia

External Links

Snippet

Existing light field based works utilize either views or focal stacks for saliency detection. However, since depth information exists implicitly in adjacent views or different focal slices, it is difficult to exploit scene depth information from both. By comparison, Epipolar Plane …
Continue reading at dl.acm.org (other versions)

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
    • G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
    • 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
    • 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
    • G06K9/34—Segmentation of touching or overlapping patterns in the image field
    • G06K9/342—Cutting or merging image elements, e.g. region growing, watershed, clustering-based techniques
    • 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
    • G06K9/32—Aligning or centering of the image pick-up or image-field
    • G06K9/3233—Determination of region of interest
    • 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
    • G06K9/68—Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
    • 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
    • G06T2207/20112—Image segmentation details
    • 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
    • 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
    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • 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
    • 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
    • G06T2207/30—Subject of image; Context of image processing
    • 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
    • G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

Similar Documents

Publication Publication Date Title
Zhuge et al. Salient object detection via integrity learning
Jing et al. Occlusion-aware bi-directional guided network for light field salient object detection
Liu et al. Poolnet+: Exploring the potential of pooling for salient object detection
Hao et al. A brief survey on semantic segmentation with deep learning
Fu et al. Siamese network for RGB-D salient object detection and beyond
Zhang et al. Road extraction by deep residual u-net
Ji et al. An improved algorithm for small object detection based on YOLO v4 and multi-scale contextual information
Zheng et al. A defect detection method for rail surface and fasteners based on deep convolutional neural network
Xu et al. Fast vehicle and pedestrian detection using improved Mask R‐CNN
Zhou et al. BCINet: Bilateral cross-modal interaction network for indoor scene understanding in RGB-D images
Cheng et al. Joint topology-preserving and feature-refinement network for curvilinear structure segmentation
Zeng et al. Reference-based defect detection network
Huang et al. Scribble-based boundary-aware network for weakly supervised salient object detection in remote sensing images
Lu et al. Occlusion-shared and feature-separated network for occlusion relationship reasoning
Chen et al. Multi-scale attention networks for pavement defect detection
Zhang et al. Discriminative feature learning for video semantic segmentation
Chu et al. Fine‐grained crack segmentation for high‐resolution images via a multiscale cascaded network
Liang et al. Context-aware network for RGB-D salient object detection
Bai et al. Circular complement network for RGB-D salient object detection
Jiang et al. Mirror complementary transformer network for RGB‐thermal salient object detection
Liang et al. MEANet: An effective and lightweight solution for salient object detection in optical remote sensing images
Hui et al. Multi-guidance CNNs for salient object detection
Yao et al. Double cross-modality progressively guided network for RGB-D salient object detection
Lu et al. Context-constrained accurate contour extraction for occlusion edge detection
Ren et al. EMF-Net: An edge-guided multi-feature fusion network for text manipulation detection