Cross-Domain Grouping and Alignment for Domain Adaptive Semantic Segmentation

Existing techniques to adapt semantic segmentation networks across the source and target domains within deep convolutional neural networks (CNNs) deal with all the samples from the two domains in a global or category-aware manner. They do not consider an inter-class variation within the target domain itself or estimated category, providing the limitation to encode the domains having a multi-modal data distribution. To overcome this limitation, we introduce a learnable clustering module, and a novel domain adaptation framework called cross-domain grouping and alignment. To cluster the samples across domains with an aim to maximize the domain alignment without forgetting precise segmentation ability on the source domain, we present two loss functions, in particular, for encouraging semantic consistency and orthogonality among the clusters. We also present a loss so as to solve a class imbalance problem, which is the other limitation of the previous methods. Our experiments show that our method consistently boosts the adaptation performance in semantic segmentation, outperforming the state-of-the-arts on various domain adaptation settings.Comment: AAAI 202

MAIR: Multi-view Attention Inverse Rendering with 3D Spatially-Varying Lighting Estimation

We propose a scene-level inverse rendering framework that uses multi-view images to decompose the scene into geometry, a SVBRDF, and 3D spatially-varying lighting. Because multi-view images provide a variety of information about the scene, multi-view images in object-level inverse rendering have been taken for granted. However, owing to the absence of multi-view HDR synthetic dataset, scene-level inverse rendering has mainly been studied using single-view image. We were able to successfully perform scene-level inverse rendering using multi-view images by expanding OpenRooms dataset and designing efficient pipelines to handle multi-view images, and splitting spatially-varying lighting. Our experiments show that the proposed method not only achieves better performance than single-view-based methods, but also achieves robust performance on unseen real-world scene. Also, our sophisticated 3D spatially-varying lighting volume allows for photorealistic object insertion in any 3D location.Comment: Accepted by CVPR 2023; Project Page is https://bring728.github.io/mair.project

Thermoelectric properties of Ca0.8Dy0.2MnO3 synthesized by solution combustion process

High-quality Ca0.8Dy0.2MnO3 nano-powders were synthesized by the solution combustion process. The size of the synthesized Ca0.8Dy0.2MnO3 powders was approximately 23 nm. The green pellets were sintered at 1150-1300°C at a step size of 50°C. Sintered Ca0.8Dy0.2MnO3 bodies crystallized in the perovskite structure with an orthorhombic symmetry. The sintering temperature did not affect the Seebeck coefficient, but significantly affected the electrical conductivity. The electrical conductivity of Ca0.8Dy0.2MnO3 increased with increasing temperature, indicating a semiconducting behavior. The absolute value of the Seebeck coefficient gradually increased with an increase in temperature. The highest power factor (3.7 × 10-5 Wm-1 K-2 at 800°C) was obtained for Ca0.8Dy0.2MnO3 sintered at 1,250°C. In this study, we investigated the microstructure and thermoelectric properties of Ca0.8Dy0.2MnO3, depending on sintering temperature

Scalar Three-point Functions in a CDL Background

Motivated by the FRW-CFT proposal by Freivogel, Sekino, Susskind and Yeh, we compute the three-point function of a scalar field in a Coleman-De Luccia instanton background. We first compute the three-point function of the scalar field making only very mild assumptions about the scalar potential and the instanton background. We obtain the three-point function for points in the FRW patch of the CDL instanton and take two interesting limits; the limit where the three points are near the boundary of the hyperbolic slices of the FRW patch, and the limit where the three points lie on the past lightcone of the FRW patch. We expand the past lightcone three-point function in spherical harmonics. We show that the near boundary limit expansion of the three-point function of a massless scalar field exhibits conformal structure compatible with FRW-CFT when the FRW patch is flat. We also compute the three-point function when the scalar is massive, and explain the obstacles to generalizing the conjectured field-operator correspondence of massless fields to massive fields.Comment: 42 pages + appendices, 10 figures; v2, v3: minor correction

Canalization of the evolutionary trajectory of the human influenza virus

Since its emergence in 1968, influenza A (H3N2) has evolved extensively in genotype and antigenic phenotype. Antigenic evolution occurs in the context of a two-dimensional 'antigenic map', while genetic evolution shows a characteristic ladder-like genealogical tree. Here, we use a large-scale individual-based model to show that evolution in a Euclidean antigenic space provides a remarkable correspondence between model behavior and the epidemiological, antigenic, genealogical and geographic patterns observed in influenza virus. We find that evolution away from existing human immunity results in rapid population turnover in the influenza virus and that this population turnover occurs primarily along a single antigenic axis. Thus, selective dynamics induce a canalized evolutionary trajectory, in which the evolutionary fate of the influenza population is surprisingly repeatable and hence, in theory, predictable.Comment: 29 pages, 5 figures, 10 supporting figure