PIA: Parallel Architecture with Illumination Allocator for Joint Enhancement and Detection in Low-Light

Visual perception in low-light conditions (e.g., nighttime) plays an important role in various multimedia-related applications (e.g., autonomous driving). The enhancement (provides a visual-friendly appearance) and detection (detects the instances of objects) in lowlight are two fundamental and crucial visual perception tasks. In this paper, we make efforts on how to simultaneously realize lowlight enhancement and detection from two aspects. First, we define a parallel architecture to satisfy the task demand for both two tasks. In which, a decomposition-type warm-start acting on the entrance of parallel architecture is developed to narrow down the adverse effects brought by low-light scenes to some extent. Second, a novel illumination allocator is designed by encoding the key illumination component (the inherent difference between normal-light and lowlight) to extract hierarchical features for assisting in enhancement and detection. Further, we make a substantive discussion for our proposed method. That is, we solve enhancement in a coarse-to-fine manner and handle detection in a decomposed-to-integrated fashion. Finally, multidimensional analytical and evaluated experiments are performed to indicate our effectiveness and superiority. The code is available at https://github.com/tengyu1998/PIA.