Spatio-temporal interactive fusion based visual object tracking method

Visual object tracking tasks often struggle with utilizing inter-frame correlation information and handling challenges like local occlusion, deformations, and background interference. To address these issues, this paper proposes a spatio-temporal interactive fusion (STIF) based visual object tracking method. The goal is to fully utilize spatio-temporal background information, enhance feature representation for object recognition, improve tracking accuracy, adapt to object changes, and reduce model drift. The proposed method incorporates feature-enhanced networks in both temporal and spatial dimensions. It leverages spatio-temporal background information to extract salient features that contribute to improved object recognition and tracking accuracy. Additionally, the model’s adaptability to object changes is enhanced, and model drift is minimized. A spatio-temporal interactive fusion network is employed to learn a similarity metric between the memory frame and the query frame by utilizing feature enhancement. This fusion network effectively filters out stronger feature representations through the interactive fusion of information. The proposed tracking method is evaluated on four challenging public datasets. The results demonstrate that the method achieves state-of-the-art (SOTA) performance and significantly improves tracking accuracy in complex scenarios affected by local occlusion, deformations, and background interference. Finally, the method achieves a remarkable success rate of 78.8% on TrackingNet, a large-scale tracking dataset

The Association between Sugar-Sweetened Beverages and Male Pattern Hair Loss in Young Men

We performed this study to investigate the association between sugar-sweetened beverage (SSB) consumption and male pattern hair loss (MPHL) in young men. We conducted this cross-sectional study from January to April 2022 in mainland China. Young people aged 18–45 years (n = 1951) were recruited from 31 provinces in China. We used a self-reported online survey for data collection. We explored the associations between the amount/frequency of SSB consumption and MPHL by using a binary logistic regression model, with adjustments for sociodemographic, hair status, dietary intake, lifestyle, and psychological factors. Among the 1028 participants (27.8 ± 7.2 years) in the final analysis, we found that high SSB consumption is associated with a higher risk of MPHL. We recommend more support to decrease SSB consumption among young people to minimize negative health outcomes