ACM Transactions on Multimedia Computing, Communications, and Applications

In this article, we address the challenging makeup transfer task, aiming to transfer makeup from a reference image to a source image while preserving facial geometry and background consistency. Existing deep neural network-based methods have shown ...

Images taken under low-light conditions suffer from poor visibility, color distortion, and graininess, all of which degrade the image quality and hamper the performance of downstream vision tasks, such as object detection and instance segmentation in the ...

Unsupervised person re-identification (Re-ID) has garnered significant attention because of its data-friendly nature, as it does not require labeled data. Existing approaches primarily address this challenge by employing feature-clustering techniques to ...

Social interaction is a common phenomenon in human societies. Different from discovering groups based on the similarity of individuals’ actions, social interaction focuses more on the mutual influence between people. Although people can easily judge ...

Multi-modal human action segmentation is a critical and challenging task with a wide range of applications. Nowadays, the majority of approaches concentrate on the fusion of dense signals (i.e., RGB, optical flow, and depth maps). However, the potential ...

Existing magnetic resonance imaging translation models rely on generative adversarial networks, primarily employing simple convolutional neural networks. Unfortunately, these networks struggle to capture global representations and contextual relationships ...

This article introduces SmoothFlowNet3D, an innovative encoder-decoder architecture specifically designed for bridging the domain gap in scene flow estimation. To achieve this goal, SmoothFlowNet3D divides the scene flow estimation task into two stages: ...

Federated learning (FL) is a prominent paradigm of 6G edge intelligence (EI), which mitigates privacy breaches and high communication pressure caused by conventional centralized model training in the artificial intelligence of things (AIoT). The execution ...

Learned video compression has drawn great attention and shown promising compression performance recently. In this article, we focus on the two components in the learned video compression framework, the conditional entropy model and quality enhancement ...

Image-based virtual try-on aims at transferring a target in-shop garment onto a reference person, and has garnered significant attention from the research communities recently. However, previous methods have faced severe challenges in handling occlusion ...

The overwhelming surge of online video platforms has raised an urgent need for social interaction recognition techniques. Compared with simple short-term actions, long-term social interactions in semantic-rich videos could reflect more complicated ...

Movie genre prediction from trailers is mostly attempted in a multi-modal manner. However, the characteristics of movie trailer audio indicate that this modality alone might be highly effective in genre prediction. Movie trailer audio predominantly ...

The objective of image captioning models is to bridge the gap between the visual and linguistic modalities by generating natural language descriptions that accurately reflect the content of input images. In recent years, researchers have leveraged deep ...

Saliency prediction (SAP) plays a crucial role in simulating the visual perception function of human beings. In practical situations, humans can quickly grasp saliency extraction in new image domains. However, current SAP methods mainly concentrate on ...

Although deep learning technique has achieved significant improvement on image compression, but its advantages are not fully explored in video compression, which leads to the performance of deep-learning-based video compression (DLVC) is obviously ...

This article focuses on motion prediction for point cloud sequences in the challenging case of deformable 3D objects, such as human body motion. First, we investigate the challenges caused by deformable shapes and complex motions present in this type of ...

Referring expression comprehension aims to align natural language queries with visual scenes, which requires establishing fine-grained correspondence between vision and language. This has important applications in multi-modal reasoning systems. Existing ...

Objective quality assessment of three-dimensional (3D) point clouds is essential for the development of immersive multimedia systems in real-world applications. Despite the success of perceptual quality evaluation for 2D images and videos, blind/no-...

In this article, we present a coding method called expanding-window zigzag decodable fountain code with unequal error protection property (EWF-ZD UEP code) to achieve scalable multimedia transmission. The key idea of the EWF-ZD UEP code is to utilize bit-...

Domain generalization primarily mitigates domain shift among multiple source domains, generalizing the trained model to an unseen target domain. However, the spurious correlation usually caused by context prior (e.g., background) makes it challenging to ...

Monocular depth estimation aims to infer a depth map from a single image. Although supervised learning-based methods have achieved remarkable performance, they generally rely on a large amount of labor-intensively annotated data. Self-supervised methods, ...

Image operators can be instrumental to computational imaging and photography. However, many of them are computationally intensive. In this article, we propose an effective yet efficient joint upsampling method to accelerate various image operators. We ...

Online cross-modal hashing has received increasing attention due to its efficiency and effectiveness in handling cross-modal streaming data retrieval. Despite the promising performance, these methods mainly focus on the supervised learning paradigm, ...

Explainable Artificial Intelligence (XAI) attempts to help humans understand machine learning decisions better and has been identified as a critical component toward increasing the trustworthiness of complex black-box systems, such as deep neural ...

Images captured under low-light conditions suffer from several combined degradation factors, including low brightness, low contrast, noise, and color bias. Many learning-based techniques attempt to learn the low-to-clear mapping between low-light and ...

A recent research direction is focused on training Deep Neural Networks (DNNs) to replicate individual subject assessments of media quality. These DNNs are referred to as Artificial Intelligence-based Observers (AIOs). An AIO is designed to simulate, in ...

Recent years have witnessed the successful application of knowledge graph techniques in structured data processing, while how to incorporate knowledge from visual and textual modalities into knowledge graphs has been given less attention. To better ...

Depression is an illness that involves emotional and mental health. Currently, depression detection through interviews is the most popular way. With the advancement of natural language processing and sentiment analysis, automated interview-based ...

High-quality image generation is an important topic in digital visualization. As a sub-topic of the research, color transfer is to produce a high-quality image with ideal color scheme learned from the reference one. In this article, we investigate the ...

Visual tracking is a fundamental task in computer vision with significant practical applications in various domains, including surveillance, security, robotics, and human-computer interaction. However, it may face limitations in visible light data, such ...