Pre-training is playing an increasingly important role in learning generic feature representation for Person Re-identification (ReID). We argue that a high-quality ReID representation should have three properties, namely, multi-level awareness, occlusion ...

Supplementing product attribute information is a critical step for E-commerce platforms, which further benefits various downstream tasks, including product recommendation, product search, and product knowledge graph construction. Intuitively, the visual ...

A wonderful piece of music is the essence and soul of dance, which motivates the study of automatic music generation for dance. To create appropriate music from dance, cross-modal correlations between dance and music such as rhythm and style, should be ...

In recent years, various distillation methods for semantic segmentation have been proposed. However, these methods typically train the student model to imitate the intermediate features or logits of the teacher model directly, thereby overlooking the high-...

The existing personalized text-to-image generation models face issues such as repeated training and insufficient generalization capabilities. We present an adaptive Style-Guided Diffusion Model (SGDM). When provided with a set of stylistically consistent ...

Medical vision-language pre-training (Med-VLP) models have recently accelerated the fast-growing medical diagnostics application. However, most Med-VLP models learn task-specific representations independently from scratch, thereby leading to great ...

Instance segmentation in medical imaging plays a crucial role in clinical diagnostic tasks, and have shown promising performance in practical applications. In this article, we discuss a more fine-grained instance segmentation task: dental structured ...

Constructing effective proxy data is one of the core challenges in data-free knowledge distillation. The existing models ignore the influence of the category entanglement of the generated data on the distillation. To alleviate this issue, imitating the ...

Generating choreography from music poses a significant challenge. Conventional dance generation methods are limited by only being able to match specific dance movements to music with corresponding rhythms, restricting the utilization of existing dance ...

Emotion recognition is essential in the diagnosis and rehabilitation of various mental diseases. In the last decade, electroencephalogram (EEG)-based emotion recognition has been intensively investigated due to its prominative accuracy and reliability, ...

The face manipulation technique such as Deepfake has been widely used to create realistic faces, which raises growing concerns in the community. Based on the correct labeled data, the current Deepfake detectors are mostly trained on the clean dataset, ...

Deep learning (DL)-based Low-dose CT (LDCT) image denoising methods may face domain shift problem, where data from different domains (i.e., hospitals) may have similar anatomical regions but exhibit different intrinsic noise characteristics. Therefore, we ...

Remote photoplethysmography (rPPG) is a non-invasive technique that aims to capture subtle variations in facial pixels caused by changes in blood volume resulting from cardiac activities. Most existing unsupervised methods for rPPG tasks focus on the ...

Text recognition remains challenging, primarily due to the scarcity of annotated real data or the hard labor to annotate large-scale real data. Most existing solutions rely on synthetic training data, where the synthetic-to-real domain gaps limit the ...

With the recent advancement of deep neural networks, visual tracking has achieved substantial progress in tracking accuracy. However, the robustness and security of tracking methods developed based on current deep models have not been thoroughly explored, ...

Text spotting in natural scenes is of increasing interest and significance due to its critical role in several applications, such as visual question answering, named entity recognition and event rumor detection on social media. One of the newly emerging ...

In recent years, the growing demand for medical imaging diagnosis has placed a significant burden on radiologists. As a solution, Medical Vision-Language Pre-training (Med-VLP) methods have been proposed to learn universal representations from medical ...

Most musical compositions utilize repetition as a fundamental element to create captivating aesthetic experiences. However, the potential of repetition in machine-learning-based algorithmic composition has not been thoroughly investigated. This article ...

Reversible data hiding-based contrast enhancement (RDHCE) can be used in contrast enhancement for medical images, and it has been a popular research topic in recent years. However, the existing RDHCE methods suffer from the problem of inaccurate ...

Owing to the rapid development of emerging 360<inline-formula><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> panoramic imaging techniques, indoor 360<inline-formula><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> ...