Results 11 to 20 of about 6,300,985 (321)
Backtracking Spatial Pyramid Pooling (SPP)-based Image Classifier for Weakly Supervised Top-down Salient Object Detection [PDF]
H. Cholakkal, J. Johnson, D. Rajan, "Backtracking Spatial Pyramid
Pooling (SPP)-based Image Classifier for Weakly Supervised Top-down Salient
Object Detection", in IEEE Transactions on Image processing, August 2018, 2016 Top-down saliency models produce a probability map that peaks at target locations specified by a task/goal such as object detection. They are usually trained in a fully supervised setting involving pixel-level annotations of objects. We propose a weakly supervised top-down saliency framework using only binary labels that indicate the presence/absence ...
Cholakkal, Hisham +2 more
arxiv +3 more sources
DISC: Deep Image Saliency Computing via Progressive Representation Learning [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2015 Salient object detection increasingly receives attention as an important component or step in several pattern recognition and image processing tasks.
Chen, Tianshui +4 more
core +2 more sources
Personalization of Saliency Estimation [PDF]
arXiv, 2017 Most existing saliency models use low-level features or task descriptions when generating attention predictions. However, the link between observer characteristics and gaze patterns is rarely investigated. We present a novel saliency prediction technique which takes viewers' identities and personal traits into consideration when modeling human ...
Yu, Bingqing, Clark, James J.
arxiv +4 more sources
Recurrent Attentional Networks for Saliency Detection [PDF]
arXiv, 2016 Convolutional-deconvolution networks can be adopted to perform end-to-end saliency detection. But, they do not work well with objects of multiple scales. To overcome such a limitation, in this work, we propose a recurrent attentional convolutional-deconvolution network (RACDNN).
Kuen, Jason, Wang, Gang, Wang, Zhenhua
arxiv +3 more sources
An Iterative Co-Saliency Framework for RGBD Images [PDF]
arXiv, 2017 As a newly emerging and significant topic in computer vision community, co-saliency detection aims at discovering the common salient objects in multiple related images. The existing methods often generate the co-saliency map through a direct forward pipeline which is based on the designed cues or initialization, but lack the refinement-cycle scheme ...
Cao, Xiaochun +6 more
arxiv +3 more sources
Real Time Image Saliency for Black Box Classifiers [PDF]
arXiv, 2017 In this work we develop a fast saliency detection method that can be applied to any differentiable image classifier. We train a masking model to manipulate the scores of the classifier by masking salient parts of the input image. Our model generalises well to unseen images and requires a single forward pass to perform saliency detection, therefore ...
Dabkowski, Piotr, Gal, Yarin
arxiv +2 more sources
Remote Sensing, 2016 The automatic detection of regions of interest (ROI) is useful for remote sensing image analysis, such as land cover classification, object recognition, image compression, and various computer vision related applications.
Jie Chen, Libao Zhang
doaj +2 more sources
CAMERAS: Enhanced Resolution And Sanity preserving Class Activation Mapping for image saliency [PDF]
Computer Vision and Pattern Recognition, 2021 Backpropagation image saliency aims at explaining model predictions by estimating model-centric importance of individual pixels in the input. However, classinsensitivity of the earlier layers in a network only allows saliency computation with low ...
M. Jalwana +3 more
semanticscholar +1 more source
PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures With Edge-Preserving Coherence [PDF]
IEEE Transactions on Image Processing, 2015 Driven by recent vision and graphics applications such as image segmentation and object recognition, computing pixel-accurate saliency values to uniformly highlight foreground objects becomes increasingly important.
Keze Wang +4 more
openalex +3 more sources
Personalized Saliency in Task-Oriented Semantic Communications: Image Transmission and Performance Analysis [PDF]
IEEE Journal on Selected Areas in Communications, 2022 Semantic communication, as a promising technology, has emerged to break through the Shannon limit, which is envisioned as the key enabler and fundamental paradigm for future 6G networks and applications, e.g., smart healthcare. In this paper, we focus on
Jiawen Kang +6 more
semanticscholar +1 more source