Electron microscopy (EM) imaging offers unparalleled resolution for analyzing neural tissues, crucial for uncovering the intricacies of synaptic connections and neural processes fundamental to understanding behavioral mechanisms. Recently, the ...

Recent advancements in end-to-end image compression demonstrate the potential to surpass traditional codecs regarding rate-distortion performance. However, current methods either prioritize human perceptual quality or solely optimize for one or a ...

As an emerging research practice leveraging recent advanced AI techniques, e.g. deep models based prediction and generation, <bold>V</bold>ideo <bold>C</bold>oding for <bold>M</bold>achines (<bold>VCM</bold>) is committed to bridging to an extent separate ...

Traditional image codecs prioritize signal fidelity and human perception, often neglecting machine vision tasks. Deep learning approaches have shown promising coding performance by leveraging rich semantic embeddings that can be optimized for both human ...

Removing the undesired moir&#x00E9; patterns from images capturing the contents displayed on screens is of increasing research interest, as the need for recording and sharing the instant information conveyed by the screens is growing. Previous demoir&#...

Colored glass, which is commonly seen in modern city life, often degrades images taken through it with co-occurring reflection and color bias due to its optical property of simultaneous transmission, reflection, and wavelength-selective absorption. ...

Cameras usually produce low-quality images under low-light conditions. Though many methods have been proposed to enhance the visibility of low-light images, they are mainly designed for illumination correction and less capable of suppressing the ...

Visual retrieval system faces frequent model update and deployment. It is a heavy workload to re-extract features of the whole database every time. Feature compatibility enables the learned new visual features to be directly compared with the old features ...

Image BERT pre-training with masked image modeling (MIM) becomes a popular practice to cope with self-supervised representation learning. A seminal work, BEiT, casts MIM as a classification task with a visual vocabulary, tokenizing the continuous ...${}^{}$${}^{}$

Vehicle Re-Identification (ReID) is of great significance for public security and intelligent transportation. Large and comprehensive datasets are crucial for the development of vehicle ReID in model training and evaluation. However, existing datasets in ...

The rapid development of modern artificial intelligence technique is mainly attributed to sufficient and high-quality data. However, in the data collection, personal privacy is at risk of being leaked. This issue can be addressed by federated learning, ...

Visual IoT (VIoT) is a promising IoT paradigm that visualizes sensing data from massive numbers of dispersed devices. A key objective in VIoT is to efficiently manage the devices to perform complex task-related visual data processing. Prior multimedia IoT ...

The ubiquitous camera networks in the city brain system grow at a rapid pace, creating massive amounts of images and videos at a range of spatial-temporal scales and thereby forming the &#x201C;biggest&#x201D; big data. However, the sensing system often ...

With the boom of the fashion market and people’s daily needs for beauty, clothing matching has gained increased research attention. In a sense, tackling this problem lies in modeling the human notions of the compatibility between fashion items, i.e., ...

With the rising incidence of some diseases, such as obesity and diabetes, the healthy diet is arousing increasing attention. However, most existing food-related research efforts focus on recipe retrieval, user-preference-based food recommendation, cooking ...

Face images captured through glass are usually contaminated by reflections. The low-transmitted reflections make the reflection removal more challenging than for general scenes because important facial features would be completely occluded. In ...

Vehicle Re-Identification (ReID) has attracted lots of research efforts due to its great significance to the public security. In vehicle ReID, we aim to learn features that are powerful in discriminating subtle differences between vehicles which are ...

Unsupervised domain adaptation (UDA) on person Re-Identification (ReID) aims to transfer the knowledge from a labeled source domain to an unlabeled target domain. Recent works mainly optimize the ReID models with pseudo labels generated by unsupervised ...

Object instance search is a challenging task with a wide range of applications, but the fast search with high accuracy has not been well solved yet. In this paper, we investigate the object instance search from a new perspective in terms of joint ...

Multi-person pose estimation has achieved great progress in recent years, even though, the precise prediction for occluded and invisible hard keypoints remains challenging. Most of the human pose estimation networks are equipped with an image ...