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A Compact Deep Architecture for Real-time Saliency Prediction
Saman Zabihi, Hamed Rezazadegan Tavakoli, Ali Borji
Saliency computation models aim to imitate the attention mechanism in the human visual system. The application of deep neural networks for saliency prediction has led to a drastic…
Shape Defense Against Adversarial Attacks
Ali Borji
Humans rely heavily on shape information to recognize objects. Conversely, convolutional neural networks (CNNs) are biased more towards texture. This is perhaps the main reason why…
Bifurcated backbone strategy for RGB-D salient object detection
Yingjie Zhai, Deng-Ping Fan, Jufeng Yang +4
Multi-level feature fusion is a fundamental topic in computer vision. It has been exploited to detect, segment and classify objects at various scales. When multi-level features mee…
Adversarial examples are useful too!
Ali Borji
Deep learning has come a long way and has enjoyed an unprecedented success. Despite high accuracy, however, deep models are brittle and are easily fooled by imperceptible adversari…
Empirical Upper Bound, Error Diagnosis and Invariance Analysis of Modern Object Detectors
Ali Borji
Object detection remains as one of the most notorious open problems in computer vision. Despite large strides in accuracy in recent years, modern object detectors have started to s…
ObjectNet Dataset: Reanalysis and Correction
Ali Borji
Recently, Barbu et al introduced a dataset called ObjectNet which includes objects in daily life situations. They showed a dramatic performance drop of the state of the art object…
Harnessing adversarial examples with a surprisingly simple defense
Ali Borji
I introduce a very simple method to defend against adversarial examples. The basic idea is to raise the slope of the ReLU function at the test time. Experiments over MNIST and CIFA…