This paper reviews the current state of the art in artificial intelligence (AI) technologies and applications in the context of the creative industries. A brief background of AI, and …
L Khachatryan, A Movsisyan… - Proceedings of the …, 2023 - openaccess.thecvf.com
Recent text-to-video generation approaches rely on computationally heavy training and require large-scale video datasets. In this paper, we introduce a new task, zero-shot text-to …
N Liu, N Zhang, K Wan, L Shao… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
Existing state-of-the-art saliency detection methods heavily rely on CNN-based architectures. Alternatively, we rethink this task from a convolution-free sequence-to …
DP Fan, GP Ji, MM Cheng… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
We present the first systematic study on concealed object detection (COD), which aims to identify objects that are visually embedded in their background. The high intrinsic similarities …
RGB-D saliency detection has attracted increasing attention, due to its effectiveness and the fact that depth cues can now be conveniently captured. Existing works often focus on …
Focusing on the issue of how to effectively capture and utilize cross-modality information in RGB-D salient object detection (SOD) task, we present a convolutional neural network …
Most salient object detection approaches use U-Net or feature pyramid networks (FPN) as their basic structures. These methods ignore two key problems when the encoder …
Deep-learning based salient object detection methods achieve great progress. However, the variable scale and unknown category of salient objects are great challenges all the time …
Being able to learn dense semantic representations of images without supervision is an important problem in computer vision. However, despite its significance, this problem …