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IEEE/CVF Conference on Computer Vision and…
Recent deep learning based approaches have shown promising results for the challenging task of inpainting large missing regions in an image. These methods can generate visually plausible image… Expand
IEEE Conference on Computer Vision and Pattern…
Salient object detection is not a pure low-level, bottom-up process. Higher-level knowledge is important even for task-independent image saliency. We propose a unified model to incorporate… Expand
IEEE Conference on Computer Vision and Pattern…
In real-world face detection, large visual variations, such as those due to pose, expression, and lighting, demand an advanced discriminative model to accurately differentiate faces from the… Expand
IEEE International Conference on Computer Vision…
We propose a highly efficient, yet powerful, salient object detection method based on the Minimum Barrier Distance (MBD) Transform. The MBD transform is robust to pixel-value fluctuation, and thus… Expand
IEEE/CVF Conference on Computer Vision and…
In this paper, we address referring expression comprehension: localizing an image region described by a natural language expression. While most recent work treats expressions as a single unit, we… Expand
Real-world applications could benefit from the ability to automatically generate a fine-grained ranking of photo aesthetics. However, previous methods for image aesthetics analysis have primarily… Expand
IEEE/CVF International Conference on Computer…
We present a generative image inpainting system to complete images with free-form mask and guidance. The system is based on gated convolutions learned from millions of images without additional… Expand
We aim to model the top-down attention of a Convolutional Neural Network (CNN) classifier for generating task-specific attention maps. Inspired by a top-down human visual attention model, we propose… Expand
IEEE International Conference on Computer Vision…
This paper investigates problems of image style, aesthetics, and quality estimation, which require fine-grained details from high-resolution images, utilizing deep neural network training approach.… Expand
In this paper, we propose a novel label propagation-based method for saliency detection. A key observation is that saliency in an image can be estimated by propagating the labels extracted from the… Expand