The construction industry is an essential component of the global economy, contributing significantly to job creation and infrastructure development. However, the industry faces several challenges, including quality issues, safety concerns, project delays, and cost overruns. There has seen a significant increase in the use of technology for construction applications in recent years. The application of modern digital technologies such as BIM, VR, AR, XR, Blockchain, IoT, Digital Twins, AI is strengthened by the emergence of visual computing and deep learning as powerful tools to address these challenges by enhancing productivity, efficiency, and safety in the industry. A comprehensive review of the literature was performed to capture an overview of the fundamental concepts of visual computing and deep learning, followed by a discussion of the challenges and opportunities presented by the construction industry. Further, an in-depth analysis is performed on the technical requirements for implementing visual computing and deep learning in the construction industry, including data acquisition, processing, and specific algorithms. Furthermore, a critical evaluation of the effectiveness of these technologies in improving construction project outcomes is discussed. The importance of adaptation of the construction industry through these technologies is examined through the accuracy of solutions proposed based on visual computing and deep learning. Overall, this review study provides a comprehensive overview of the current state of visual computing and deep learning in construction and offers insights into their potential for future development and growth.