1.4k citations · 4.4k across the 74 of their papers we have counts for
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An Unsupervised Game-Theoretic Approach to Saliency Detection
Yu Zeng, Huchuan Lu, Ali Borji +1
We propose a novel unsupervised game-theoretic salient object detection algorithm that does not require labeled training data. First, saliency detection problem is formulated as a…
Structure-measure: A New Way to Evaluate Foreground Maps
Deng-Ping Fan, Ming-Ming Cheng, Yun Liu +2
Foreground map evaluation is crucial for gauging the progress of object segmentation algorithms, in particular in the filed of salient object detection where the purpose is to accu…
Statistics of Deep Generated Images
Yu Zeng, Huchuan Lu, Ali Borji
Here, we explore the low-level statistics of images generated by state-of-the-art deep generative models. First, Variational auto-encoder (VAE~\cite{kingma2013auto}), Wasserstein g…
Negative Results in Computer Vision: A Perspective
Ali Borji
A negative result is when the outcome of an experiment or a model is not what is expected or when a hypothesis does not hold. Despite being often overlooked in the scientific commu…
Human-like Clustering with Deep Convolutional Neural Networks
Ali Borji, Aysegul Dundar
Classification and clustering have been studied separately in machine learning and computer vision. Inspired by the recent success of deep learning models in solving various vision…
Saliency Revisited: Analysis of Mouse Movements versus Fixations
Hamed R. Tavakoli, Fawad Ahmed, Ali Borji +1
This paper revisits visual saliency prediction by evaluating the recent advancements in this field such as crowd-sourced mouse tracking-based databases and contextual annotations.…
What are the Receptive, Effective Receptive, and Projective Fields of Neurons in Convolutional Neural Networks?
Hung Le, Ali Borji
In this work, we explain in detail how receptive fields, effective receptive fields, and projective fields of neurons in different layers, convolution or pooling, of a Convolutiona…
Paying Attention to Descriptions Generated by Image Captioning Models
Hamed R. Tavakoli, Rakshith Shetty, Ali Borji +1
To bridge the gap between humans and machines in image understanding and describing, we need further insight into how people describe a perceived scene. In this paper, we study the…