Unsupervised Deraining: Where Asymmetric Contrastive Learning Meets Self-similarity

Most of the existing learning-based deraining methods are supervisedly trained on synthetic rainy-clean pairs. The domain gap between the synthetic and real rain makes them less generalized to complex real rainy scenes. Moreover, the existing methods mainly utilize the property of the image or rain layers independently, while few of them have considered their mutually exclusive relationship. To solve above dilemma, we explore the intrinsic intra-similarity within each layer and inter-exclusiveness between two layers and propose an unsupervised non-local contrastive learning (NLCL) deraining method. The non-local self-similarity image patches as the positives are tightly pulled together, rain patches as the negatives are remarkably pushed away, and vice versa. On one hand, the intrinsic self-similarity knowledge within positive/negative samples of each layer benefits us to discover more compact representation; on the other hand, the mutually exclusive property between the two layers enriches the discriminative decomposition. Thus, the internal self-similarity within each layer (similarity) and the external exclusive relationship of the two layers (dissimilarity) serving as a generic image prior jointly facilitate us to unsupervisedly differentiate the rain from clean image. We further discover that the intrinsic dimension of the non-local image patches is generally higher than that of the rain patches. This motivates us to design an asymmetric contrastive loss to precisely model the compactness discrepancy of the two layers for better discriminative decomposition. In addition, considering that the existing real rain datasets are of low quality, either small scale or downloaded from the internet, we collect a real large-scale dataset under various rainy kinds of weather that contains high-resolution rainy images.Comment: 16 pages, 15 figures. arXiv admin note: substantial text overlap with arXiv:2203.1150

High-speed high-resolution plasma spectroscopy using spatial-multiplex coherence imaging techniques

We have recently obtained simultaneous two-dimensional (2D) plasmaDoppler spectroscopic images of plasma brightness, temperature, and flow fields. Using compact polarization optical methods, quadrature images of the optical coherence of an isolated spectral line are multiplexed to four quadrants of a fast charge-coupled device camera. The simultaneously captured, but distinct, images can be simply processed to unfold the plasma brightness, temperature, and flow fields. This static system, which is a spatial-multiplex variant of previously reported electro-optically modulated, temporal-multiplex coherence imaging systems, is based on a high-throughput imagingpolarizationinterferometer that employs crossed Wollaston prisms and appropriate image plane masks. Because the images are captured simultaneously, it is well suited to high-spectral-resolution, high-throughput 2D imaging of transient or rapidly changing spectroscopic scenes. To illustrate instrument performance we present recent results using a static 4-quadrant Dopplercoherence imaging on the H-1 heliac at the ANU.This work has been, in part, supported by the Australian Government Department of Education, Science and Training under the International Science Linkages program, Grant No. CG050061

OAFuser: Towards Omni-Aperture Fusion for Light Field Semantic Segmentation of Road Scenes

Light field cameras can provide rich angular and spatial information to enhance image semantic segmentation for scene understanding in the field of autonomous driving. However, the extensive angular information of light field cameras contains a large amount of redundant data, which is overwhelming for the limited hardware resource of intelligent vehicles. Besides, inappropriate compression leads to information corruption and data loss. To excavate representative information, we propose an Omni-Aperture Fusion model (OAFuser), which leverages dense context from the central view and discovers the angular information from sub-aperture images to generate a semantically-consistent result. To avoid feature loss during network propagation and simultaneously streamline the redundant information from the light field camera, we present a simple yet very effective Sub-Aperture Fusion Module (SAFM) to embed sub-aperture images into angular features without any additional memory cost. Furthermore, to address the mismatched spatial information across viewpoints, we present Center Angular Rectification Module (CARM) realized feature resorting and prevent feature occlusion caused by asymmetric information. Our proposed OAFuser achieves state-of-the-art performance on the UrbanLF-Real and -Syn datasets and sets a new record of 84.93% in mIoU on the UrbanLF-Real Extended dataset, with a gain of +4.53%. The source code of OAFuser will be made publicly available at https://github.com/FeiBryantkit/OAFuser.Comment: The source code of OAFuser will be made publicly available at https://github.com/FeiBryantkit/OAFuse

A versatile quantum walk resonator with bright classical light

In a Quantum Walk (QW) the "walker" follows all possible paths at once through the principle of quantum superposition, differentiating itself from classical random walks where one random path is taken at a time. This facilitates the searching of problem solution spaces faster than with classical random walks, and holds promise for advances in dynamical quantum simulation, biological process modelling and quantum computation. Current efforts to implement QWs have been hindered by the complexity of handling single photons and the inscalability of cascading approaches. Here we employ a versatile and scalable resonator configuration to realise quantum walks with bright classical light. We experimentally demonstrate the versatility of our approach by implementing a variety of QWs, all with the same experimental platform, while the use of a resonator allows for an arbitrary number of steps without scaling the number of optics. Our approach paves the way for practical QWs with bright classical light and explicitly makes clear that quantum walks with a single walker do not require quantum states of light