[PDF] Top 20 Salient Object Detection Via Two Stage Graphs
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Salient Object Detection Via Two Stage Graphs
... Sparse representation (SR) theory has been applied in salient object detection due to its efficiency. SR based methods first construct an over-complete dictionary. Then, the input image is sparsely ... See full document
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Deep Embedding Features for Salient Object Detection
... 4 stage-wise saliency predictions in one ...these stage-wise ...4) stage results as RFIN ...and stage-wise predictions, RFIN can effectively reduce the error of last ... See full document
8
Deep salient object detection with contextual information guidance
... Earlier salient object detection methods mainly compute saliency based on hand-crafted features [7]–[14], ...saliency detection and have achieved substantial improve- ments due to their ... See full document
16
SuperVAE: Superpixelwise Variational Autoencoder for Salient Object Detection
... then stage-wisely refine the prediction results of the last recurrent ...to detection errors when the salient object consists of several different ... See full document
8
Salient object detection employing robust sparse representation and local consistency
... imposing two Laplacian regularizations on the representation coefficients and reconstruction ...resulting salient ob- ject detection model is formulated as ... See full document
31
Using High-Dimensional Color Transform To Detection Of Salient Region Via Local Spatial Support
... detect salient regions. These models can detect salient regions of an image uniformly with low computational ...into two parts—a low-rank matrix and sparse noise—where the former explains the ... See full document
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I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge Graphs
... edge graphs (KGs) have been successfully used in various computer vision tasks such as object detection (Fang et ...knowledge graphs for ... See full document
9
Semantic Segmentation and Object Detection Based On Active Contour Model and Fuzzy Clustering
... are two fundamental techniques computer vision utilizes to reach its ...the salient and coherent regions that semantically belong to different ...and object detection play the essential role ... See full document
128
RGB T salient object detection via fusing multi level CNN features
... a salient object detection method by introducing a series of short connections between shallower and deeper side-output ...for salient object detection, which first integrated ... See full document
16
A new efficient active contour model without local initializations for salient object detection
... local maximums on the object edges and then the stopping function can be relatively far from zero on the edges, and the curve may pass through the boundary. Also, the local maximums of the discrete gradient ... See full document
13
A Two stage Approach for Extending Event Detection to New Types via Neural Networks
... In the ACE 2005 corpus, the event type Move- ment only has one subtype of Transport which mainly focuses on the transportation of weapons, vehicles or people. The context of the trigger words of the subtype Transport ... See full document
8
Salient Region Detection via Integrating Diffusion-Based Compactness and Local Contrast
... on two different graphs to detect the salient seed ...for object saliency using a diffusion ...an object saliency map f = [ f1, f2, · · · , fN ]T ...the two most commonly used ... See full document
12
Detection of Complex Salient Regions
... Visual saliency [1] is a broad term that refers to the idea that certain parts of a scene are preattentively distinctive and create some form of immediate significant visual arousal within the early stages of the human ... See full document
11
Salient Object Detection via Structured Matrix Decomposition
... for salient object detection, where a matrix is decomposed into a low-rank matrix representing image background and a sparse matrix identifying salient ...objects. Two deficiencies, ... See full document
15
Background prior-based salient object detection via deep reconstruction residual
... on salient object detection and is one of art methods, we treat it as the baseline method in this group of ...our two processing steps have often been adopted in other art saliency ... See full document
14
Salient Object Detection via Combining Duplex Features
... The result of SLIC super-pixel segmentation is a similarly uniform region, which ensures the spatial distribution of pixels within each region. The result of K-Means clustering only guarantees the similarity of the color ... See full document
8
Adaptive Feature Fusion Object Tracking with Kernelized Correlation Filters
... filtering object tracker MOSSE uses gray feature as object descriptor, but gray feature is easily affected by environmental factors, such as noise and illumination, ...the object tracking ...the ... See full document
10
AUTOMATED IMAGE RETARGETTING AND CROPPING USING SALIENCY DETECTION AUTOMATIC CONTEXT AWARE CROPPING
... the salient region and remove the unwanted ...on salient object detection and remove the extra background which is not of equal importance as the salient ... See full document
14
Deep Learning for Mango (Mangifera Indica) Panicle Stage Classification
... There are two reports on the use of machine vision to assess mango flowering. [19] and [20] used the traditional method of pixelwise segmentation to segment panicle pixels from canopy pixels, with results ... See full document
21
Effect of Salient Features in Object Recognition
... Table 3: SURF Results with and without saliency on UIUC dataset.Number of images used for training=200, and number of images used for test=50 Category.. SURF without Saliency.[r] ... See full document
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