RESUMEN
Exemplar-based colorization aims to generate plausible colors for a grayscale image with the guidance of a color reference image. The main challenging problem is finding the correct semantic correspondence between the target image and the reference image. However, the colors of the object and background are often confused in the existing methods. Besides, these methods usually use simple encoder-decoder architectures or pyramid structures to extract features and lack appropriate fusion mechanisms, which results in the loss of high-frequency information or high complexity. To address these problems, this paper proposes a lightweight semantic attention-guided Laplacian pyramid network (SAGLP-Net) for deep exemplar-based colorization, exploiting the inherent multi-scale properties of color representations. They are exploited through a Laplacian pyramid, and semantic information is introduced as high-level guidance to align the object and background information. Specially, a semantic guided non-local attention fusion module is designed to exploit the long-range dependency and fuse the local and global features. Moreover, a Laplacian pyramid fusion module based on criss-cross attention is proposed to fuse high frequency components in the large-scale domain. An unsupervised multi-scale multi-loss training strategy is further introduced for network training, which combines pixel loss, color histogram loss, total variance regularisation, and adversarial loss. Experimental results demonstrate that our colorization method achieves better subjective and objective performance with lower complexity than the state-of-the-art methods.
RESUMEN
Motivated by a combination of social media, technological evolution, as well as new habits and preferences of TV content consumers, there is an increasing demand for enhancement of professional productions with user generated content. Studies have explored the potential and feasibility of this approach, indicating that footage from non-professionals can be effectively used to enrich the viewing experience. However, an important concern is whether such efforts are appealing to potential contributors, and what can actually impact their satisfaction and loyalty. Aiming to investigate these factors, this paper presents a mobile application for content contributors and a study involving 38 attendees of live events, using the application in the field. The events were hosted in two different countries, and transmitted by two well-known broadcasters. The results suggest that age, gender, technological expertise, and overall sharing attitude do not affect the satisfaction and loyalty of contributors. The differentiating factors, however, are the filming confidence and expertise of contributors, as well as the Wi-Fi/4G connectivity on-site. Implications of these findings are discussed and recommendations for similar endeavors are provided.