The project MULTICLOD adresses recognition in stereoscopic video of various traffic environments. We study local and global image representations based on cues extracted by combining classification and reconstruction approaches. Our goal is to devise novel multi-class and weakly supervised recognition models capable of contributing to various applications in the fields of smart vehicles and intelligent transportation systems.