Real-World Image Variation by Aligning Diffusion Inversion Chain

Recent diffusion model advancements have enabled high-fidelity images to be generated using text prompts. However, a domain gap exists between generated images and real-world images, which poses a challenge in generating high-quality variations of real-world images. Our investigation uncovers that this domain gap originates from a latents' distribution gap in different diffusion processes. To address this issue, we propose a novel inference pipeline called Real-world Image Variation by ALignment (RIVAL) that utilizes diffusion models to generate image variations from a single image exemplar. Our pipeline enhances the generation quality of image variations by aligning the image generation process to the source image's inversion chain. Specifically, we demonstrate that step-wise latent distribution alignment is essential for generating high-quality variations. To attain this, we design a cross-image self-attention injection for feature interaction and a step-wise distribution normalization to align the latent features. Incorporating these alignment processes into a diffusion model allows RIVAL to generate high-quality image variations without further parameter optimization. Our experimental results demonstrate that our proposed approach outperforms existing methods with respect to semantic-condition similarity and perceptual quality. Furthermore, this generalized inference pipeline can be easily applied to other diffusion-based generation tasks, such as image-conditioned text-to-image generation and example-based image inpainting.Comment: 19 pages; Project page: https://rival-diff.github.io/ Code(release later): https://github.com/julianjuaner/RIVAL

Ref-NPR: Reference-Based Non-Photorealistic Radiance Fields for Controllable Scene Stylization

Current 3D scene stylization methods transfer textures and colors as styles using arbitrary style references, lacking meaningful semantic correspondences. We introduce Reference-Based Non-Photorealistic Radiance Fields (Ref-NPR) to address this limitation. This controllable method stylizes a 3D scene using radiance fields with a single stylized 2D view as a reference. We propose a ray registration process based on the stylized reference view to obtain pseudo-ray supervision in novel views. Then we exploit semantic correspondences in content images to fill occluded regions with perceptually similar styles, resulting in non-photorealistic and continuous novel view sequences. Our experimental results demonstrate that Ref-NPR outperforms existing scene and video stylization methods regarding visual quality and semantic correspondence. The code and data are publicly available on the project page at https://ref-npr.github.io.Comment: Accepted by CVPR2023. 17 pages, 20 figures. Project page: https://ref-npr.github.io, Code: https://github.com/dvlab-research/Ref-NP

High channel count and high precision channel spacing multi-wavelength laser array for future PICs

Multi-wavelength semiconductor laser arrays (MLAs) have wide applications in wavelength multiplexing division (WDM) networks. In spite of their tremendous potential, adoption of the MLA has been hampered by a number of issues, particularly wavelength precision and fabrication cost. In this paper, we report high channel count MLAs in which the wavelengths of each channel can be determined precisely through low-cost standard μm-level photolithography/holographic lithography and the reconstruction-equivalent-chirp (REC) technique. 60-wavelength MLAs with good wavelength spacing uniformity have been demonstrated experimentally, in which nearly 83% lasers are within a wavelength deviation of ±0.20 nm, corresponding to a tolerance of ±0.032 nm in the period pitch. As a result of employing the equivalent phase shift technique, the single longitudinal mode (SLM) yield is nearly 100%, while the theoretical yield of standard DFB lasers is only around 33.3%

GridFormer: Towards Accurate Table Structure Recognition via Grid Prediction

All tables can be represented as grids. Based on this observation, we propose GridFormer, a novel approach for interpreting unconstrained table structures by predicting the vertex and edge of a grid. First, we propose a flexible table representation in the form of an MXN grid. In this representation, the vertexes and edges of the grid store the localization and adjacency information of the table. Then, we introduce a DETR-style table structure recognizer to efficiently predict this multi-objective information of the grid in a single shot. Specifically, given a set of learned row and column queries, the recognizer directly outputs the vertexes and edges information of the corresponding rows and columns. Extensive experiments on five challenging benchmarks which include wired, wireless, multi-merge-cell, oriented, and distorted tables demonstrate the competitive performance of our model over other methods.Comment: ACMMM202

Constant bandwidth ORAM with small block size using PIR operations

Recently, server-with-computation model has been applied in Oblivious RAM scheme to achieve constant communication (constant number of blocks). However, existing works either result in large block size O(log^6N), or have some security flaws. Furthermore, a lower bound of sub-logarithmic bandwidth was given if we do not use expensive fully homomorphic operations. The question of \whether constant bandwidth with smaller block size without fully homomorphic operations is achievable remains open. In this paper, we provide an affirmative answer. We propose a constant bandwidth ORAM scheme with block size O(log^3N) using only additive homomorphic operations. Our scheme is secure under the standard model. Technically, we design a non-trivial oblivious clear algorithm with very small bandwidth to improve the eviction algorithm in ORAM for which the lower bound proof does not apply. As an additional benefit, we are able to reduce the server storage due to the reduction in bucket size

On-chip topological transport of optical frequency combs in silicon-based valley photonic crystals

The generation and control of optical frequency combs in integrated photonic systems enables complex, high-controllable, and large-scale devices. In parallel, harnessing topological physics in multipartite systems has allowed them with compelling features such as robustness against fabrication imperfections. Here we experimentally demonstrate on-chip topological transport for optical frequency combs at telecommunication wavelengths, both in classical and nonclassical domains. We access both the quantum frequency combs and dissipative Kerr soliton combs with a micro-resonator. The quantum frequency comb, that is, a coherent superposition of multiple frequency modes, is proven to be a frequency-entangled qudit state. We also show that dissipative Kerr soliton combs are highly coherent and mode-locked due to the collective coherence or self-organization of solitons. Moreover, the valley kink states allow both quantum frequency combs and dissipative Kerr soliton combs with robustness against sharp bends. Our topologically protected optical frequency combs could enable the inherent robustness in integrated complex photonic systems.Comment: 20 pages,12 figure

Global Impact Dynamic Modeling and Verification of a Flexible Beam with Large Overall Motion

The theoretical modeling, numerical simulation, and experimental verification for the impact dynamics of a flexible beam with large overall motion are researched. Based on the rigid-flexible coupling dynamic theory of flexible multibody system, the rigid-flexible coupling dynamic equations of the beam are established. On the use of the continuous contact force method (CCFM) and the contact constraint method (CCM), the respective global impact dynamic equations of the system are derived to achieve dynamic transformation and solution in different stages including impact and unimpact status. The experimental study on the impact dynamics of the flexible beam is investigated, and the dynamic response in the impact process is obtained. The experimental results are compared with the results of the impact dynamic simulation and the finite element method (FEM) simulation. The system's dynamic behaviors in the impact process are analyzed, and the accuracy of the two impact dynamic theories is verified

Hotspot Detection and Spatiotemporal Evolution of Catering Service Grade in Mountainous Cities from the Perspective of Geo-Information Tupu

Catering services are an essential part of urban life. The spatial structure and evolution of catering services can reflect the characteristics of an urban structure to a certain extent. In this study, we selected the main urban area of Chongqing, a typical mountainous city, as the research area. According to data sources for 200,000 catering POI data points in 2015 and 2020, we extracted the hotspots according to catering service grade based on kernel density. We quantitatively analyzed the spatiotemporal structure of catering services in the mountainous city. In addition, we used digital field hierarchical structure Tupu and generalized symmetric structure Tupu to identify the spatial morphology and evolution characteristics to enhance the understanding of geoscience trends. The results showed that (1) the distribution of catering services was statically consistent with the “multi-center group” distribution of the mountainous city and dynamically similar to the “sprawling leap” development of the mountainous city where it developed from independent points to cross mountains and rivers. Moreover, we found that there was a tendency of adhering development between groups. (2) From the perspective of symmetrical distribution, the symmetrical distribution of the catering industry reflected a certain generalized symmetrical structure with mountains and rivers in the mountainous city. Furthermore, the city tended to develop symmetrically along the topography, thus forming the symmetry of economic geography

Scaling Effects of Elevation Data on Urban Nonpoint Source Pollution Simulations

The scale effects of digital elevation models (DEM) on hydrology and nonpoint source (NPS) pollution simulations have been widely reported for natural watersheds but seldom studied for urban catchments. In this study, the scale effect of DEM data on the rainfall-runoff and NPS pollution was studied in a typical urban catchment in China. Models were constructed based on the DEM data of nine different resolutions. The conventional model performance indicators and the information entropy method were applied together to evaluate the scale effects. Based on the results, scaling effects and a resolution threshold of DEM data exist for urban NPS pollution simulations. Compared with natural watersheds, the urban NPS pollution simulations were primarily affected by the local terrain due to the overall flat terrain and dense sewer inlet distribution. The overland process simulation responded more sensitively than the catchment outlet, showing prolonged times of concentration for impervious areas with decreasing DEM resolution. The diverse spatial distributions and accumulation magnitudes of pollutants could lead to different simulation responses to scaling effects. This paper provides information about the specific characteristics of the scale effects of DEM data in a typical urban catchment, and these results can be extrapolated to other similar catchments as a reference for data collection