This paper presents a real-time application of see-through technology using computer vision (e.g., object detection) and Vehicle-to-X (V2X) communication (e.g., Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I)). Each access point (AP) was connected to Chattanooga’s fiber optics internet, supporting a data transfer rate up to 10-Gbps. Using a 5Ghz frequency, vehicular communications were set up with a seamless handover for transferring real-time data. Two web cameras acting as clients were mounted on the windshield of two of three vehicles to send image data to the offsite server. Using multi-threaded programming, both image feeds were processed simultaneously. Once the server received the images, it performed an object recognition algorithm on each image using a convolutional neural network (CNN). Post- identification, the images from the second vehicle were sent and overlaid dynamically to the third vehicle’s image. This repetitive overlapping of images allowed the third vehicle to “see-through” the second vehicle in real-time. This experiment was showcased during the US Ignite Smart Cities Summit in June 2017 to emphasize the benefits of drivers being able to “see-through” the car in front to make more intelligent decisions when passing a vehicle, stopping for a pedestrian, or seeing an upcoming detour due to construction before the view is within their line of sight. Using V2X communication with computer vision gives the driver a higher level of awareness and allows better decision making in the case of a roadway conflict, ultimately increasing the level of safety on our roadways.