Changes In Appearance Research Articles

When Hyaluronic Acid Alters its Rheology: Clinical, Ultrasonographic and Pathological Correlation

Hyaluronic acid has demonstrated itself as a highly successful non-invasive medical procedure for mitigating facial aging changes. This success is primarily attributed to its biodegradable or temporary nature, the reproducibility of aesthetic results, and the potential for dissolution through hyaluronidase. Despite its virtues, changes in the rheology of the product can occur, leading to alterations in its structure, resulting in the formation of visible, palpable nodules that are challenging to degrade with hyaluronidase. We present a case series of 9 patients in whom high-resolution ultrasound detected changes in the normal echographic appearance of hyaluronic acid suggestive of pseudosolidification, including increased echogenicity, a hyperechoic band inside the periphery of the deposits, the absence of degradation changes, and persistent, well-defined oval morphology. All cases showed no inflammatory activity on Doppler. In one case, the deposit was surgically removed during blepharoplasty, and histopathological analysis provided useful information to understand the mechanisms behind such complications.

Parasites make hosts more profitable but less available to predators

Parasites are omnipresent, and their eco‐evolutionary significance has aroused much interest from scientists. Parasites may affect their hosts in many ways with changes in density, appearance, behaviour and energy content, likely to modify their value to predators (profitability) within the optimal foraging framework. Consequently, parasites could impact predators' diet and the trophic links through food webs. Here, we investigate the consequences of the infection by the iridovirus Daphnia iridescent virus 1 (DIV‐1) on the reproductive success, mortality, appearance, mobility, and biochemical composition of water fleas Daphnia magna, a widespread freshwater crustacean. We do predation tests and compare search time, handling time and feeding preference between infected and uninfected Daphnia when preyed upon by Notonecta sp., a common aquatic insect. Our findings show that infection does not change fecundity but reduces lifespan and thereby constrains fitness. Infected Daphnia show reduced mobility and increased color reflectance in the UV and visible domains, which potentially affects their appearance and thus vulnerability to predators. Infection increases body size and the amount of proteins but does not affect carbohydrate and lipid contents. Although infected Daphnia are longer to handle, they are preferred over uninfected individuals by aquatic insects. Taken together, our findings show that DIV‐1 infection could make Daphnia more profitable to predators (24% energy increase), a positive effect that should be balanced with a lower availability due to the higher mortality of infected specimens. We also highlight that exposure to infection in asymptomatic individuals leads to ecological characteristics that differ from both healthy and symptomatic infected individuals.

Paediatric Cushing's disease: long-term outcome and predictors of recurrence.

Paediatric Cushing's disease (CD) is characterized by excess ACTH secretion from a pituitary adenoma, leading to hypercortisolism. It has approximately 5% of the incidence of adult CD and is a rare disorder in the paediatric age range. The four most specific presenting features of hypercortisolism are: change in facial appearance, weight gain, decreased linear growth and virilisation shown by advanced pubic hair for the stage of breast development or testicular volume. The main diagnostic priority is the demonstration of hypercortisolism followed by distinction between its ACTH-dependent and ACTH-independent origin, thus leading to identification of aetiology. All treatment options aim to resolve or control hypercortisolism. Consensus favours transsphenoidal (TSS) pituitary surgery with selective removal of the corticotroph adenoma. TSS in children with CD is now well established and induces remission in 70-100% of cases. External pituitary radiotherapy and bilateral adrenalectomy are second-line therapeutic approaches in subjects not responding to TSS. Long-term medical treatment is less frequently adopted. Recurrence in paediatric CD cases is low with factors predicting relapse being higher post-TSS cortisol and ACTH levels and rapid recovery of the hypothalamic-pituitary-adrenal axis after TSS. In summary, complete excision of the microadenoma with histological and biochemical evidence for this, predicts a low rate of recurrence of CD. Due to the need for rapid diagnosis and management to avoid the burden of prolonged exposure to hypercortisolism, tertiary university centres comprising both paediatric and adult endocrinology specialists together with experienced pituitary surgery and, eventually, radiotherapy units are recommended for referral of these patients.

Lightweight Spatial-Temporal Contextual Aggregation Siamese Network for Unmanned Aerial Vehicle Tracking

Benefiting from the powerful feature extraction capability of deep learning, the Siamese tracker stands out due to its advanced tracking performance. However, constrained by the complex backgrounds of aerial tracking, such as low resolution, occlusion, similar objects, small objects, scale variation, aspect ratio change, deformation and limited computational resources, efficient and accurate aerial tracking is still difficult to realize. In this work, we design a lightweight and efficient adaptive temporal contextual aggregation Siamese network for aerial tracking, which is designed with a parallel atrous module (PAM) and adaptive temporal context aggregation model (ATCAM) to mitigate the above problems. Firstly, by using a series of atrous convolutions with different dilation rates in parallel, the PAM can simultaneously extract and aggregate multi-scale features with spatial contextual information at the same feature map, which effectively improves the ability to cope with changes in target appearance caused by challenges such as aspect ratio change, occlusion, scale variation, etc. Secondly, the ATCAM adaptively introduces temporal contextual information to the target frame through the encoder-decoder structure, which helps the tracker resist interference and recognize the target when it is difficult to extract high-resolution features such as low-resolution, similar objects. Finally, experiments on the UAV20L, UAV123@10fps and DTB70 benchmarks demonstrate the impressive performance of the proposed network running at a high speed of over 75.5 fps on the NVIDIA 3060Ti.

Incidental Thalamic Lesions Identified on Brain MRI in Pediatric and Young Adult Patients: Imaging Features and Natural History.

Nonspecific, localized thalamic signal abnormalities of uncertain significance are occasionally found on pediatric brain MR imaging. The goal of this study is to describe the MR imaging appearance and natural history of these lesions in children and young adults. This retrospective study evaluated clinically acquired brain MR imaging examinations obtained from February 1995 to March 2022 at a large, tertiary care pediatric hospital. Examinations with non-mass-like and nonenhancing thalamic lesions were identified based on term search of MR imaging reports. A total of 221 patients formed the initial group for imaging assessment. Additional exclusions during imaging review resulted in 171 patients. Imaging appearance and size changes were assessed at baseline and at follow-up examinations. A total of 171 patients (102 male) at a median age of 11 years (range: 1-23 years), 568 MR imaging examinations, and 180 thalamic lesions were included. Median time from baseline to the last follow-up MR imaging was 542 days (range: 46-5730 days). No lesion enhanced at any time point. On imaging follow-up, 11% of lesions (18/161) became smaller, 10% (16/161) resolved, 73% (118/161) remained stable, and 6% (9/161) increased in size at some point during evaluation. Median time interval from baseline to enlargement was 430 days (range: 136-1074 days). Most incidental, non-mass-like thalamic signal abnormalities were stable, decreased in size, or resolved on follow-up imaging and are likely of no clinical significance. Surveillance strategies with longer follow-up intervals may be adequate in the management of such findings.

The presence and distribution of various genes in postnatal CLP-affected palatine tissue

BackgroundWorldwide cleft lip with or without a cleft palate (CL/P) is the most common craniofacial birth defect. Apart from changes in facial appearance, additionally affected individuals often suffer from various associated comorbidities requiring complex multidisciplinary treatment with overall high expenses. Understanding the complete pathogenetic mechanisms of CL/P might aid in developing new preventative strategies and therapeutic approaches, help with genetic counselling, and improve quality of life. Many genes have been associated with the development of orofacial clefts; however, the majority require further research. Based on the role of PAX7, PAX9, SHH, SOX3, WNT3A, and WNT9B in orofacial development, the intention was to use chromogenic in situ hybridization to detect the six genes in postnatal CLP-affected palatine tissue and compare their distribution within the tissue samples.ResultsStatistically significant differences in the distribution of PAX7, PAX9, WNT3A, and WNT9B were observed. In total, 19 pairs of moderate to very strong positive correlations were noted.ConclusionsChanges in the cleft-affected palatine epithelium primarily seem to be associated with the PAX7 gene; however, PAX9, WNT3A, WNT9B, and SOX3 role seems to be more limited. Whilst connective tissue changes seem to depend on PAX7 only, SHH seems to participate individually and indistinctly. Numerous positive correlations reflect the complicating interactions of the pathways and their components in the orofacial cleft morphopathogenesis.

Deep learning and multi-modal fusion for real-time multi-object tracking: Algorithms, challenges, datasets, and comparative study

Real-time multi-object tracking (MOT) is a complex task involving detecting and tracking multiple objects. After the objects are detected, they are assigned markers, and their trajectories are tracked in real-time. The scientific community is intrigued by the possibilities of utilizing MOT technology in the context of smart cities. Their primary focus lies in the domains of intelligent transportation, detection of vehicles and pedestrians, crowd surveillance, and public safety. Deep learning techniques have been developed in recent years to effectively tackle the challenges of real-time MOT tasks and enhance tracking performance. Environmental perception within smart traffic applications relies heavily on sensor data fusion. In traffic scenarios, a thoughtful approach involves utilizing a combination of sensors and cameras to detect and track targets while gathering valuable data effectively. However, it faces challenges when it comes to detecting and tracking objects that are in motion, have complex changes in appearance, or are in crowded scenes. This paper explores the foundational standard for real-time Multiple Object Tracking tasks. We prioritize the examination of quantitative measures by conducting a comprehensive analysis of widely utilized benchmark datasets and metrics. This study also investigates established embedding techniques and multi-modal fusion methods within real-time multi-target tracking algorithms. Each strategy will be classified and assessed according to a predefined set of principles. The paper presents a comprehensive analysis and visual representation of various MOT strategies. Finally, this paper aims to present an overview of the current challenges faced by the MOT mission, as well as the potential objectives that lie ahead.

Odour reduction of kraft lignin by wet oxidation

This study assesses wet oxidation of partially concentrated Kraft black liquor (40% dry matter) as a method for odour reduction of the lignin obtained from it by acid precipitation. To this end, and for the first time ever, the effects of wet oxidation temperature (120–150 ºC) and pressure (10–50 bar) on the odour profile of both the black liquor and the acid precipitated lignin were analysed. 2-methoxyphenol, dimethyl disulphide and dimethyl trisulphide were the main responsible compounds of the black liquor odour and, in the case of the precipitated lignin, aldehydes and organic acids also contributed. The most odourless lignin was the one precipitated from Kraft black liquor oxidised at the most severe conditions tested (150 °C and 50 bar for 2 h). However, these also caused a reduction in the lignin yield, as well as significant compositional and appearance changes, thus limiting its use in certain fields.

Siamese Tracking Network with Spatial-Semantic-Aware Attention and Flexible Spatiotemporal Constraint

Siamese trackers based on classification and regression have drawn extensive attention due to their appropriate balance between accuracy and efficiency. However, most of them are prone to failure in the face of abrupt motion or appearance changes. This paper proposes a Siamese-based tracker that incorporates spatial-semantic-aware attention and flexible spatiotemporal constraint. First, we develop a spatial-semantic-aware attention model, which identifies the importance of each feature region and channel to target representation through the single convolution attention network with a loss function and increases the corresponding weights in the spatial and channel dimensions to reinforce the target region and semantic information on the target feature map. Secondly, considering that the traditional method unreasonably weights the target response in abrupt motion, we design a flexible spatiotemporal constraint. This constraint adaptively adjusts the constraint weights on the response map by evaluating the tracking result. Finally, we propose a new template updating the strategy. This strategy adaptively adjusts the contribution weights of the tracking result to the new template using depth correlation assessment criteria, thereby enhancing the reliability of the template. The Siamese network used in this paper is a symmetric neural network with dual input branches sharing weights. The experimental results on five challenging datasets show that our method outperformed other advanced algorithms.

Study on anti-inflammatory effect of Shangkehuangshui in vitro and in vivo based on TLR4/TLR2-NF-κB signaling pathway

Ethnopharmacological relevanceShangkehuangshui (SK) has been traditionally used to treat traumatic injury, soft tissue and bone injury in Foshan hospital of traditional Chinese medicine for more than 60 years, which composed of many Chinese herbs such as Coptis chinensis Franch., Gardenia jasminoides Ellis, Phellodendron chinense Schneid. and etc. SK exhibits heat-clearing and detoxifying, enhancing blood circulation to eliminate blood stasis properties, and demonstrates noteworthy clinical efficacy. Nevertheless, the underlying mechanism remains uncertain. Aim of the studyThe early study found that SK had good anti-inflammatory effects in acute soft tissue injury model. This research is to verify the anti-inflammatory properties of SK both in vitro and in vivo via TLR4/TLR2-NF-κB signaling pathway, to clarify the underlying mechanisms responsible for the curative effect of SK. MethodsThe RAW264.7 cells inflammatory model was established with lipopolysaccharide (LPS) in vitro. NO and TNF-α, IL-6, IL-1β were determined with Griess method and ELISA method respectively. The mRNA and protein expression levels of TLR4/TLR2-NF-κB pathway were evaluated by qPCR and Western blot method. In vivo experiment, chronic soft tissue injury rat models were established by tracking gastrocnemius muscle with electrical stimulation, then local appearance and pathological changes were observed and recorded, the contents of inflammatory factors in serum and tissue were performed. Moreover, we also measured and contrasted the expression of TLR4/TLR2-NF-κB related factors. ResultsSK effectively inhibited the LPS-induced generation of inflammatory cytokines, including NO, TNF-α, IL-6 and IL-1β in RAW264.7 cells, and significantly suppressed the expression of TLR4, TLR2, MyD88, IκB, and NF-κB. In vivo, SK remarkably decreased the damage appearance scores after 4 and 14 days of administration and inhibit the quantity of NO and leukocytes present in the serum. Additionally, the inflammatory infiltration in the pathological section was alleviated, myofibrillar hyperplasia and blood stasis were reduced. SK markedly downregulated NO, TNF-α, IL-6 and IL-1β in injured tissues of rats, also declined the expression of TLR4, TLR2, MyD88, IκB, NF-κB, IL-6, TNF-α and IL-1β. ConclusionThis study revealed that SK had obvious effects of anti-inflammatory actions in vivo and vitro, effectively reduced acute and chronic soft tissue injury in clinical, this might be attributed to inhibit the TLR4/TLR2-NF-κB pathway, further inhibit the expression of downstream relevant pro-inflammatory cytokines.

The love of beauty: aesthetic standards in the six dynasties and the enhancement of appearance in the Shangqing scriptures

ABSTRACT During Early Medieval China, aristocratic groups experienced changes in their standards of emphasis on body aesthetics. During this period, appearance was a necessary standard of reference for aristocrats when evaluating people; as a result, the aristocracy emphasized appearance and the pursuit of improving it. These social changes affected the religious sphere. Shangqing Daoism, popular among aristocratic groups in the Southern Dynasty, had a pronounced tendency to cater to such a change. In order to convince the aristocracy, Daoists of the Shangqing movement argued that their practices would improve even one’s external appearance. This article summarizes the transformation and meanings of the aristocracy’s body aesthetic standards, especially for men, during this period and discusses the influence of this transformation on Daoism, especially the Shangqing tradition. Some scriptures claim that by using their methods, the practitioner’s body will change over time, which is very much in line with aristocratic beauty standards. The change in appearance is both the result of the practitioner’s pursuit and the proof that the practitioner is on the right track of the Dao.

An overview of the research of the Records of the Grand Historian (Shiji) in South Korea over the past forty years (1971–2010)

The Shiji (史記 Records of the Grand Historian) is a pathbreaking monument of Chinese history. Its author Sima Qian 司馬遷 created a genre of biography centered around individuals that was continually used in dynastic histories from the Han dynasty onward. Sima Qian's composition of the Shiji not only respected historical facts and directly portrayed them as they occurred, but also paid attention to featuring polished language and beautiful writing. He organically integrated different styles of narrative, expressions, and reasoning and achieved a high degree of uniformity of thought and art, providing a model for later generations of literature and history. The Shiji was not only a pioneer in the genre of Chinese biographical history, but also had a far-reaching impact on later prose, fiction, and drama. It was also soon transmitted overseas and had a large effect on countries in the Chinese cultural sphere. With the introduction of the Shiji to Korea, Korean intellectuals particularly showed interest in and reverence for the work, and it was highly valued in the Korean academic world. By the mid-1960s, with the development of the national economy, all of South Korean society entered a new period of history that not only saw fundamental changes in the nation's appearance, but also saw academic and cultural affairs return to the right track, and at that time South Korean academics renewed their high degree of interest in learning about and researching Chinese academics and culture. It was on this foundation that South Korean intellectuals made great advances in translating and studying the Shiji and made positive contributions to its transmission, spread, and popularization. After briefly reviewing the transmission of the Shiji in Korea, this paper reviews the state of translation and study of the Shiji in South Korea from the nearly four decades from 1971 to 2010 and offers an objective evaluation of some shortcomings and gaps in this research.

Examining Changes in Taiwan’s New Graduates Through Self-Portraiture Process Research (Examen des changements chez les nouveaux diplômés de Taiwan grâce à la recherche sur le processus d’autoportrait)

New graduates face challenges in job hunting, causing them to doubt their professional abilities and professional performance. The issues of adaptation influence work satisfaction and employee retention. This phenomenological study explored the changes in self-esteem and personal appearance using self-portraits in art therapy. The researchers recruited five new female college graduates (ages 20–25 years) who experienced frustration, low self-esteem, and negative personal appearance in the workplace. We integrated Glaister’s serial self-portraits and Betensky’s phenomenological art therapy practical technical steps to conduct six sessions of an art therapy course with self-portraits as the main axis of creation. Phenomenological study was adopted and Hycner’s (1985) phenomenological analysis steps were applied in this study. The change process observed in the self-portraiture by participants is summarized in three stages: “Opening the Door to Creation: Entering One’s Changing Process of Creating a Self-Portrait,” “Exploring the Realm of Self: To Explore the Process of Drawing a Self-Portrait With Self-awareness,” and “Key Elements of Changing Opportunities: The Self-Portrait Brings Changing Opportunities Regarding Self-Esteem and Personal Appearance.” The results indicate that when individuals overcome their fear of creating self-portraits, they begin to find symbolic meanings such as concrete self-image related to personal issues, personal appearance, or control in work, in the process. The results and limitations of this study are discussed. Future research might consider the use of self-portraits in art therapy process so that new graduates can enhance their control in the work and include male participants to understand their status and process.

The impact of fatigue severity and depression level on the quality of life in individuals with Parkinson's disease in Taiwan.

Patients diagnosed with Parkinson's disease undergo alterations in physical, psychological, and social functionality, with the psychological domain being particularly predisposed to inducing fatigue and depressive symptoms. Understanding the alterations occurring within a patient's body and mind and how these influence their overall quality of life is crucial. This study sought to explore the predictive capacity of fatigue severity, the presence of depressive symptoms, and diverse demographic factors on the quality of life among individuals with Parkinson's disease. A cross-sectional correlational study was conducted at a teaching hospital in southern Taiwan. The research utilized a questionnaire survey to interview 133 study participants, focusing on the Quality of Life Scale, Depression Scale, Fatigue Severity Scale, Social Support Scale, and demographic attributes. A total of 130 valid questionnaires were obtained. The results showed that Hoehn and Yahr stage, fatigue severity, and depression status could predict quality of life, explaining 51.1% of the total variance. These findings suggest that patients at advanced Hoehn and Yahr stages, experiencing more severe fatigue, and exhibiting higher levels of depression, tended to report a lower overall quality of life. Our findings suggest that, in addition to Hoehn and Yahr stage, the severity of fatigue and levels of depression significantly impact the quality of life in individuals with Parkinson's disease. Nurses need to understand the "stressful life events" and the changes in appearance and physical function that patients with Parkinson's disease face due to chronic degenerative diseases. Hence, apart from addressing patients' physiological needs, healthcare professionals should also offer appropriate care for psychological issues, such as depressive symptoms. Encouraging patients to participate in "counseling groups" can further bolster their social support networks, enhancing their overall well-being and addressing comorbidities associated with chronic degenerative diseases.

WiAi-ID: Wi-Fi-Based Domain Adaptation for Appearance-Independent Passive Person Identification

Wi-Fi signal-based person identification has become a hot research topic due to the widespread deployment of Wi-Fi devices and the fact that these approaches are non-contact, passive, and privacy-preserving. While the existing related methods and systems have achieved good performance for person identification, they also encounter many significant challenges in practical applications. Due to the propagation properties of Wi-Fi signals, the signal at the receiver will change significantly when the user’s appearance changes. This makes single-appearance trained models unusable for cross-appearance recognition tasks. To address this challenge, we propose a deep learning-based framework for appearance-independent identification using Wi-Fi signals (WiAi-ID), the core of which lies in the fact that the domain discriminator and feature extractor are trained together in an adversarial manner, thus forcing the model to extract identity-inherent features independent of human appearance, and introduces a multi-scale CNN adaptation module to capture time-span-based features. We collected Wi-Fi signal data of pedestrians with different appearances. The experimental results show that WiAi-ID can effectively eliminate the impact on identification due to pedestrian appearance variations and accordingly outperforms the current state-of-the-art video and wireless signal-based recognition methods.

The effect of facial ageing on forensic facial image comparison

AbstractFacial appearance changes over time as people age. This poses a challenge for individuals working in forensic settings whose role requires them to match the identity of face images. The present research aimed to determine how well an international sample of forensic facial examiners could match faces with a substantial age gap. We tested a sample of 60 facial examiners, 23 professional teams, and 81 untrained control participants. Participants matched pairs of photographs with a 10–30‐year age gap between the images. Participants also estimated the ages of the faces. On the matching task, individual professionals, and teams outperformed controls and made fewer high confidence errors. On the age estimation task, there was no advantage for professionals relative to controls. Our results suggest that forensic facial examiners can tolerate substantial age differences between adult faces when performing comparisons, but this advantage does not extend to accurate age estimation.

Multi-Modal Fusion Based on Depth Adaptive Mechanism for 3D Object Detection

Lidars and cameras are critical sensors for 3D object detection in autonomous driving. Despite the increasing popularity of sensor fusion in this field, accurate and robust fusion methods are still under exploration due to non-homogenous representations. In this paper, we find that the complementary roles of point clouds and images vary with depth. An important reason is that the point cloud appearance changes significantly with increasing distance from the Lidar, while the image's edge, color, and texture information are not sensitive to depth. To address this, we propose a fusion module based on the Depth Attention Mechanism (DAM), which mainly consists of two operations: gated feature generation and point cloud division. The former adaptively learns the importance of bimodal features without additional annotations, while the latter divides point clouds to achieve differential fusion of multi-modal features at different depths. This fusion module can enhance the representation ability of original features for different point sets and provide more comprehensive features by using the dual splicing strategy of concatenation and index connection. Additionally, considering point density as a feature and its negative correlation with depth, we build an Adaptive Threshold Generation Network (ATGN) to generate the depth threshold by extracting density information, which can divide point clouds more reasonably. Experiments on the KITTI dataset demonstrate the effectiveness and competitiveness of our proposed models.

One-Stream Vision-Language Memory Network for Object Tracking

Most existing tracking methods try to represent the target by exploiting visual information as much as possible based on the various deep networks. However, the appearance model hardly describes the attribute feature of the target well, which makes the trackers fail to adapt to the complex visual surrounding. In this paper, inspired by brain-like intelligence, we propose an One-stream Vision-Language Memory network (OVLM) for object tracking. Firstly, we use the combination of vision and language to build the target model and use the semantic information in the language to compensate for the instability of visual information, making the target model more stable in the face of complex appearance changes. Secondly, to build a more compact target model, we propose a memory token selection mechanism that utilizes linguistic information to eliminate tokens that do not contain target information. Furthermore, to provide better visual information for target modeling, we propose a language-based evaluation method to select high-quality target samples to be stored in the memory. Finally, OVLM achieves a 64.7% success rate on the large-scale tracking benchmark dataset TNL2K, outperforming the previous best result (VLT) by 11.6%. By exposing the possibility of the vision-language memory network, we aim to draw greater attention to it and open up new avenues for vision-language tracking.

RGB-T Tracking with Template-Bridged Search Interaction and Target-Preserved Template Updating.

The goal of RGB-Thermal (RGB-T) tracking is to utilize the synergistic and complementary strengths of RGB and TIR modalities to enhance tracking in diverse situations, with cross-modal interaction being a crucial element. Earlier methods often simply combine the features of the RGB and TIR search frames, leading to a coarse interaction that also introduced unnecessary background noise. Many other approaches sample candidate boxes from search frames and apply different fusion techniques to individual pairs of RGB and TIR boxes, which confines cross-modal interactions to local areas and results in insufficient context modeling. Additionally, mining video temporal contexts is also under-explored in RGB-T tracking. To alleviate these limitations, we propose a novel Template-Bridged Search region Interaction (TBSI) module that exploits templates as the medium to bridge the cross-modal interaction between RGB and TIR search regions by gathering and distributing target-relevant object and environment contexts. An Illumination Guided Fusion (IGF) module is designed to adaptively fuse RGB and TIR search region tokens with a global illumination factor. Furthermore, in the inference stage, we also propose an efficient Target-Preserved Template Updating (TPTU) strategy, leveraging the temporal context within video sequences to accommodate the target's appearance change. Our proposed modules are integrated into a ViT backbone for joint feature extraction, search-template matching, and cross-modal interaction. Extensive experiments on three popular RGB-T tracking benchmarks demonstrate our method achieves new state-of-the-art performances. Code is available at https://github.com/RyanHTR/TBSI.

Part-based Tracking via Discriminative Correlation Filters

In order to better deal with the partial occlusion issue, part-based trackers are widely used in visual object tracking recently. However, it is still difficult to realize fast and robust tracking, due to complicated online training and updating process. Correlation filters have been used in visual object tracking tasks recently because of their high efficiency. However, the traditional correlation filter based tracking methods do not deal with occlusion well. In this paper, we propose a novel tracking method which tracks objects based on parts with multiple correlation filters. The Bayesian inference framework and a structural constraint mask are adopted to enable our tracker to be robust to various appearance changes. Additionally, a discriminative part selection scheme is adopted to further improve performance and accelerate our method. Experimental results demonstrate that our multiple part tracker can significantly improve tracking performance on benchmark datasets.