Image Saliency Prediction in Novel Production Scenarios.

Predicting image saliency has many potential useful applications across several industries, including film production, creative marketing content, product design, and quality control in manufacturing. Although image saliency prediction, in general, has made substantial progress with the advent of deep learning on benchmark datasets, it still has room to improve when applied to novel scenarios. This paper presents our experimental findings in dataset building and model development for predicting saliency of cinematic images in a real-world context. To evaluate the proposed model, we conducted experiments on both benchmark datasets (i.e., SALICON, MIT1003, MIT300, CAT2000) as well as a private dataset. The results demonstrate the superior performance of our proposed method. We highlight a film production use case, but the model and methods explored here may also generalize to other areas relevant to image saliency.