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DeepUSPS: Deep Robust Unsupervised Saliency Prediction With Self-Supervision
[article]
2021
arXiv
pre-print
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These labels are refined incrementally in multiple iterations via our proposed self-supervision technique. ...
In this work, we propose a two-stage mechanism for robust unsupervised object saliency prediction, where the first stage involves refinement of the noisy pseudo labels generated from different handcrafted ...
DeepUSPS: Deep Unsupervised saliency prediction via self-supervision In this section, we explain the technical details of components in the overall pipeline shown in Fig. 3 . ...
arXiv:1909.13055v4
fatcat:wdx3l53gczcsnbdk4t6ed366ae
Characterizing and Improving the Robustness of Self-Supervised Learning through Background Augmentations
[article]
2021
arXiv
pre-print
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We also make progress in completely unsupervised saliency detection, in the process of generating saliency masks used for background augmentations. ...
Recent progress in self-supervised learning has demonstrated promising results in multiple visual tasks. ...
Unsupervised Saliency Detection: DeepUSPS 2 In order to train a completely unsupervised saliency detector, we build upon DeepUSPS , a recent state-of-the-art weakly supervised saliency detection method ...
arXiv:2103.12719v2
fatcat:qaxu7ypdmvcqjez6s5hx3s6slq
Object Segmentation Without Labels with Large-Scale Generative Models
[article]
2021
arXiv
pre-print
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The recent rise of unsupervised and self-supervised learning has dramatically reduced the dependency on labeled data, providing effective image representations for transfer to downstream vision tasks. ...
Namely, we show that recent unsupervised GANs allow to differentiate between foreground/background pixels, providing high-quality saliency masks. ...
To compare with deep saliency detection models, we also add DeepUSPS (Nguyen et al., 2019) to the list of baselines. ...
arXiv:2006.04988v2
fatcat:nt3ae3lbsra3tbqwyu5stoce64
Distilling Localization for Self-Supervised Representation Learning
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2004.06638v1 fatcat:uq7qr3wxbfh3zn44zqbrf5wtha
With this approach (DiLo), significant performance is achieved for self-supervised learning on ImageNet classification, and also for object detection on PASCAL VOC and MSCOCO. ...
Recent progress in contrastive learning has revolutionized unsupervised representation learning. ...
saliency prediction via selfsupervision. ...
arXiv:2004.06638v2
fatcat:36x43zh5vvg3pbsvak7wf3nwci
Few-Cost Salient Object Detection with Adversarial-Paced Learning
[article]
2021
arXiv
pre-print
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The file type is application/pdf.
A fundamental challenge in training the existing deep saliency detection models is the requirement of large amounts of annotated data. ...
Essentially, APL is derived from the self-paced learning (SPL) regime but it infers the robust learning pace through the data-driven adversarial learning mechanism rather than the heuristic design of the ...
In light of the advanced development in deep learning, recent salient object detection methods mainly adopted the CNN models to learn saliency patterns under a fully supervised fashion. ...
arXiv:2104.01928v1
fatcat:vrcarkcjtrbgxfiii4znjdqz34