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We propose Latent Diffusion-Enhanced 3D Gaussian Splatting (LatentDiff-3DGS) model, an extension of 3D Gaussian Splatting (3DGS) that incorporates pretrained latent diffusion models to enhance the visual quality of novel view synthesis. By ...

Large-scale datasets with point-wise semantic and instance labels are crucial to 3D instance segmentation but also expensive. To leverage unlabeled data, previous semi-supervised 3D instance segmentation approaches have explored self-training frameworks, ...

We developed PathActMarker, an R package for inferring pathway activity of complex diseases. The package integrates widely used normalization methods for gene expression data and provides pathway data from six sources. Meanwhile, eight state-of-...

3D content creation has long been a complex and time-consuming process, often requiring specialized skills and resources. While recent advancements have allowed for text-guided 3D object and scene generation, they still fall short of providing sufficient ...

Multi-passage machine reading comprehension (MRC) aims to answer a question by multiple passages. Existing multi-passage MRC approaches have shown that employing passages with and without golden answers (i.e., labeled and unlabeled passages) for model ...

We design ABLB (Adaptive Block Load Balancing), a switch-based adaptive routing load balancing mechanism based on the granularity of the flow block and aware of PFC pauses in RDMA networks. We evaluate ABLB with the NS-3 simulator under the collective ...

This article delves into the integration and sharing methods of spatial geographic informatioDue to the characteristics of multi-source, multi-scale, and multi temporal spatial geographic data, and the widespread dispersion, repetitive layout, and ...

Class-agnostic motion prediction methods aim to comprehend motion within open-world scenarios, holding significance for autonomous driving systems. However, training a high-performance model in a fully-supervised manner always requires substantial ...

We study the problem of synthesizing a long-term dynamic video from only a single image. This is challenging since it requires consistent visual content movements given large camera motions. Existing methods either hallucinate inconsistent perpetual ...

In the context of the COVID-19 epidemic, a “double-hazard scenario” consisting of a natural disaster and a public health event occurring simultaneously is likely to arise. Focusing on this double-hazard scenario, this study developed a ...

We study the problem of novel view synthesis of objects from a single image. Existing methods have demonstrated the potential in single-view view synthesis. However, they still fail to recover the fine appearance details, especially in self-...

Neural Radiance Field (NeRF) and its variants have exhibited great success on representing 3D scenes and synthesizing photo-realistic novel views. However, they are generally based on the pinhole camera model and assume all-in-focus inputs. This limits ...

Temporal consistency is the key challenge of video depth estimation. Previous works are based on additional optical flow or camera poses, which is time-consuming. By contrast, we derive consistency with less information. Since videos inherently exist ...

Enhanced index tracking (EIT) is a popular form of investment strategy, which seeks to create a portfolio to generate excess return relative to a given benchmark index without purchasing all the index components. In this paper we ...

• A lower partial moment framework for the enhanced index tracking (EIT) problem.

This research studies the optimal consumption, investment, and life insurance choices for a wage earner with habit formation, inflation risk, and mortality risk. The wage earner has access to a risk-free asset, an index bond, and a stock in a financial ...

Identifying biomarkers of heterogeneous complex diseases has always been one of the focuses in medical research. In previous studies, the powerful network propagation methods have been applied to finding marker genes related to specific diseases, but ...

Breast cancer is a heterogeneous disease with many clinically distinguishable molecular subtypes each corresponding to a cluster of patients. Identification of prognostic and heterogeneous biomarkers for breast cancer is to detect cluster-specific gene ...

In this paper, by splitting a traffic flow series into basis series and deviation series, the concepts of similarity and repeatability of traffic flow patterns are defined using the statistic average values of the basis series and the deviation series and ...

By using wavelet transform modulus maxima method to detection image edge, edge details are easily smoothed out in the large scale analysis and related parameters great influenced by the noise is not easy to extract in traditional small scale analysis. ...

This paper presents an improved region growing method. Firstly, the automatic seed region growing method is used in this paper to overcome the blindness for selecting the seed pixels. Secondly, the Normalized Cut (N-cut) method is used between the ...