7 accepted papers
Most data-driven deep learning-based Artistic Image Aesthetics Assessment (AIAA) methods cannot effectively extract visual attributes from art images since the existing artistic image datasets don’t provide any information about visual attributes. The lack of visual attributes reduces the interpreta…
No-Reference Image Quality Assessment (NR-IQA) is a fundamental computer vision task. In this paper, we propose a new Attention-Enhanced Feature Fusion Network for NR-IQA (AEFF-IQA) that integrates multi-scale local and non-local features. Firstly, multi-scale local and non-local features containing…
Fine-grained image retrieval (FGIR) is an important topic of image retrieval, and its challenge lies in the accurate identification of image objects with minor inter-class differences and considerable intraclass differences. Most existing methods exploit Convolutional Neural Networks (CNNs) to captu…
Self-supervised video hashing aims at generating hash codes and performing fast video content retrieval by leveraging the visual content information inherent in the videos themselves. Most existing methods often overlook the structure-preserving information within the visual content of the videos an…
Prompt learning was proposed to solve the problem of inconsistency between the upstream and downstream tasks and has achieved State-Of-The-Art (SOTA) results in various Natural Language Processing (NLP) tasks. However, Relation Extraction (RE) is more complex than other text classification tasks, wh…
A practical long-term tracker typically contains three key properties, i.e., an efficient model design, an effective global re-detection strategy and a robust distractor awareness mechanism. However, most state-of-the-art long-term trackers (e.g., Pseudo and re-detecting based ones) do not take all…
Despite the great success of Siamese-based trackers, their performance under complicated scenarios is still not satisfying, especially when there are distractors. To this end, we propose a novel Siamese relation network, which introduces two efficient modules, i.e. Relation Detector (RD) and Refinem…