Background Prior-Based Salient Object Detection via Deep Reconstruction Residual

By Junwei Han, Dingwen Zhang, Xintao Hu, Lei Guo, Jinchang Ren, Feng Wu. 2015

449 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

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In Computer Vision and Pattern Recognition

Citations in the corpus

CNNs-Based RGB-D Saliency Detection via Cross-View Transfer and Multiview Fusion (2018, unknown): “[24] modeled the background by”
Distilling Localization for Self-Supervised Representation Learning (2020, background): “Useful priors include background priors (Han et al. 2014), color contrast priors (Cheng et al.”
Weakly supervised target detection in remote sensing images based on transferred deep features and negative bootstrapping (2015, methodology): “Finally, a post-processing scheme is used to eliminate repeated detections via non-maximum suppression (Cheng et al. 2013b, 2014; Han et al. 2015a, 2014; Zhang et al. 2015).”
Semantic Annotation of High-Resolution Satellite Images via Weakly Supervised Learning (2016, unknown): “In contrast, rather than directly using low-level features, shallow unsupervised feature learning methods, such as sparse coding [6], [53] and sparse autoencoders [2], [54], [55], were exploited to learn midlevel features [36] for scene classification or target detection [37].”
Revealing Event Saliency in Unconstrained Video Collection (2017, unknown): “As can be seen, event saliency is different from the visual saliency [3]–[5] as event saliency is towards higher-level semantic interpretation of the video content.”
New Contour Cue-Based Hybrid Sparse Learning for Salient Object Detection (2019, unknown): “Besides the above traditional approaches, deep learning has recently been adopted to extract salient features or directly learn saliency scores from raw images, such as LEGS [42], super-CNN [43], and SDAE [44].”
DHSNet: Deep Hierarchical Saliency Network for Salient Object Detection (2016, methodology): “Background prior [9-11] hypothesizes that regions near image boundaries are probably backgrounds.”
Progressively Complementarity-Aware Fusion Network for RGB-D Salient Object Detection (2018, background): “* Corresponding author contexts and the difficulty in exploring saliency-specific prior knowledge, a large body of deep convolutional neural networks (CNNs) [11-17] have been designed for RGB-induced salient object detection and have achieved appealing performance.”
Salient Band Selection for Hyperspectral Image Classification via Manifold Ranking (2016, background): “in many applications [4]–[6], such as multimedia retrieval, object detection, video compression, and image resizing.”
Breast cancer detection using deep convolutional neural networks and support vector machines (2019, methodology): “DCNN has achieved success in image classification problems including image analysis as in ( Han et al., 2015 ; Zabalza et al., 2016 ).”
Two-Stage Learning to Predict Human Eye Fixations via SDAEs (2016, background): “Motivated by the evidence that locations in the visual field that are distinctive from their surroundings are more likely to attract human attention, most existing fixation prediction models mainly deal with the problem of measuring the distinctiveness at a location [13]–[16].”
Advanced Deep-Learning Techniques for Salient and Category-Specific Object Detection: A Survey (2018, background): “One of the earliest pioneering works is [45], where Han et al.”