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cs.CV2020

Image Captioning through Image Transformer

Sen He, Wentong Liao, Hamed R. Tavakoli +3

Automatic captioning of images is a task that combines the challenges of image analysis and text generation. One important aspect in captioning is the notion of attention: How to d…

cs.CV2019

Understanding and Visualizing Deep Visual Saliency Models

Sen He, Hamed R. Tavakoli, Ali Borji +2

Recently, data-driven deep saliency models have achieved high performance and have outperformed classical saliency models, as demonstrated by results on datasets such as the MIT300…

cs.CV2019

Human Attention in Image Captioning: Dataset and Analysis

Sen He, Hamed R. Tavakoli, Ali Borji +1

In this work, we present a novel dataset consisting of eye movements and verbal descriptions recorded synchronously over images. Using this data, we study the differences in human…

cs.CV2018

What Catches the Eye? Visualizing and Understanding Deep Saliency Models

Sen He, Ali Borji, Yang Mi +1

Deep convolutional neural networks have demonstrated high performances for fixation prediction in recent years. How they achieve this, however, is less explored and they remain to…

cs.CV2018

Aggregated Sparse Attention for Steering Angle Prediction

Sen He, Dmitry Kangin, Yang Mi +1

In this paper, we apply the attention mechanism to autonomous driving for steering angle prediction. We propose the first model, applying the recently introduced sparse attention m…

cs.CV2018

Salient Region Segmentation

Sen He, Nicolas Pugeault

Saliency prediction is a well studied problem in computer vision. Early saliency models were based on low-level hand-crafted feature derived from insights gained in neuroscience an…