CONTINUOUS DEPTH MAP RECONSTRUCTION FROM LIGHT FIELDS

Light field analysis recently received growing interest, since its rich structure information benefits many computer vision tasks. This paper presents a novel method to reconstruct continuous depth maps from light field data. Conventional approaches usually treat depth map reconstruction as an optimization problem with discrete labels. On the contrary, our proposed method can obtain continuous depth maps by solving a linear system, which preserves richer details compared with conventional discrete approaches. Structure tensor is employed to extract raw depth information and corresponding confidence levels from the light field data. We introduce a method to reduce the adverse effect of unreliable local estimations, which helps to get rid of errors in specular areas and edges where depth values are discontinuous. Experiments on both synthetic and real light field data demonstrate the effectiveness of the proposed method. Index Terms — Depth map reconstruction, light field, linear system 1

A Unified Approach to Robust Inference for Genetic Covariance

Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex traits. Many complex traits are found to have shared genetic etiology. Genetic covariance is defined as the underlying covariance of genetic values and can be used to measure the shared genetic architecture. The data of two outcomes may be collected from the same group or different groups of individuals and the outcomes can be of different types or collected based on different study designs. This paper proposes a unified approach to robust estimation and inference for genetic covariance of general outcomes that may be associated with genetic variants nonlinearly. We provide the asymptotic properties of the proposed estimator and show that our proposal is robust under certain model mis-specification. Our method under linear working models provides robust inference for the narrow-sense genetic covariance, even when both linear models are mis-specified. Various numerical experiments are performed to support the theoretical results. Our method is applied to an outbred mice GWAS data set to study the overlapping genetic effects between the behavioral and physiological phenotypes. The real data results demonstrate the robustness of the proposed method and reveal interesting genetic covariance among different mice developmental traits

Soil Liquid Limit and Plastic Limit Treating System Based on Analytic Method

AbstractAccording to two present China national standards, a software as Soil Liquid Limit and Plastic Limit Data Treating System, with analytic method, was developed using object-oriented visual programming tool. The analytic method used in the developed system was different to traditional method of treating soil liquid limit and plastic limit data. N-S algorithm flowchart demonstrated that switch statement and condition statement were taken as main algorithm and second level select nested structure was taken as main frame for the developed system. Three kinds of soil specimens were tested with liquid and plastic limit combined test and the test data was treated with graphic method, Excel software and Soil Liquid Limit and Plastic Limit Data Treating System. The comparative conclusion indicated that Soil Liquid Limit and Plastic Limit Data Treating System improved efficiency and accuracy evidently for treating soil liquid and plastic limit data and had advantages of easy operation and high reliability

Convolutional Initialization for Data-Efficient Vision Transformers

Training vision transformer networks on small datasets poses challenges. In contrast, convolutional neural networks (CNNs) can achieve state-of-the-art performance by leveraging their architectural inductive bias. In this paper, we investigate whether this inductive bias can be reinterpreted as an initialization bias within a vision transformer network. Our approach is motivated by the finding that random impulse filters can achieve almost comparable performance to learned filters in CNNs. We introduce a novel initialization strategy for transformer networks that can achieve comparable performance to CNNs on small datasets while preserving its architectural flexibility.Comment: 14 pages, 9 figures, 8 table

Combinando video y programación: el papel de la programación en un video musical interactivo

[ES] La tecnología de programación ha jugado un papel importante en el desarrollo de los videojuegos en los últimos años. Por otro lado, estamos asistiendo a un cambio paulatino en el modo de ver películas, el sistema tradicional no puede satisfacer la demanda de entretenimiento de la audiencia, más acorde con el planteamiento del vídeo musical interactivo que surge en cierta medida como alternativa al tradicional. La idea de este proyecto está inspirada en el proyecto de película interactiva de ¿Black Mirror: Bandersnatch¿ lanzada por Netflix a finales de 2018. En ella se aplica un método interactivo relacionado con el videojuego ofreciéndonos un engañoso control sobre los personajes y el desarrollo de la historia. Este trabajo se enmarca dentro de la creación de un producto interactivo, realizado junto a Zakaria Bouassa (un alumno también del máster), en el que la audiencia podrá experimentar distintas sensaciones emocionales observando diferentes vídeos. En el desarrollo de las diferentes opciones se utilizará una descripción de los ambientes psicológicos en dos frecuencias de energía (alta o baja) y de afecto (positivo o negativo) para ir generando diferentes combinaciones de vídeo que se asociará a los diferentes elementos del producto interactivo. La responsabilidad principal de la parte de programación es organizar y fusionar los videoclips a través del software de programación. Se usará el software Unity para crear interfaces de ventana, botones de opción y guiar la dirección de conexión de videoclips. La estructura utilizada para el Desarrollo del programa ha sido la de árbol binario.[EN] Programming technology has played an important role in the development of video games in recent years. On the other hand, we are witnessing a gradual change in the way we watch movies, the traditional system cannot satisfy the audience's demand for entertainment, more in line with the approach of interactive music video that arises to some extent as an alternative to the traditional one. The idea of this project is inspired by the interactive film project of "Black Mirror: Bandersnatch" launched by Netflix at the end of 2018, in which an interactive method related to the video game is applied, offering us virtual control over the characters and the development of the history. This work is part of the creation of an interactive product, carried out together with Zakaria Bouassa (another student from the same master), in which the audience will be able to experience different emotional sensations through watching different videos. For the development of these different options, a description of the psychological environments in two frequencies of energy (high or low) and affect (positive or negative) will be used to generate different video combinations that will be associated with the different elements of the interactive product. The main responsibility of the programming part is to organize and merge the video clips through the programming software. Unity software will be used to create window interfaces, buttons, and guide the direction of the video clip. The binary tree structure was used for the development of this software.Li, J. (2020). Combinando video y programación: el papel de la programación en un video musical interactivo. Universitat Politècnica de València. http://hdl.handle.net/10251/150000TFG

A unified formulation for circle and polygon concrete-filled steel tube columns under axial compression

Current design practice of concrete-filled steel tube (CFST) columns uses different formulas for different section profiles to predict the axial load bearing capacity. It has always been a challenge and practically important issue for researchers and design engineers who want to find a unified formula that can be used in the design of the columns with various sections, including solid, hollow, circular and polygonal sections. This has been driven by modern design requirements for continuous optimization of structures in terms of not only the use of materials, but also the topology of structural components. This paper extends the authors’ previous work [1] on a unified formulation of the axial load bearing capacity for circular hollow and solid CFST columns to, now, including hollow and solid CFST columns with regular polygonal sections. This is done by taking a circular section as a special case of a polygonal one. Finally, a unified formula is proposed for calculating the axial load bearing capacity of solid and hollow CFST columns with either circular or polygonal sections. In addition, laboratory tests on hollow circular and square CFST long columns are reported. These results are useful addition to the very limited open literature on testing these columns, and are also as a part of the validation process of the proposed analytical formulas

NaturalConv: A Chinese Dialogue Dataset Towards Multi-turn Topic-driven Conversation

In this paper, we propose a Chinese multi-turn topic-driven conversation dataset, NaturalConv, which allows the participants to chat anything they want as long as any element from the topic is mentioned and the topic shift is smooth. Our corpus contains 19.9K conversations from six domains, and 400K utterances with an average turn number of 20.1. These conversations contain in-depth discussions on related topics or widely natural transition between multiple topics. We believe either way is normal for human conversation. To facilitate the research on this corpus, we provide results of several benchmark models. Comparative results show that for this dataset, our current models are not able to provide significant improvement by introducing background knowledge/topic. Therefore, the proposed dataset should be a good benchmark for further research to evaluate the validity and naturalness of multi-turn conversation systems. Our dataset is available at https://ai.tencent.com/ailab/nlp/dialogue/#datasets.Comment: Accepted as a main track paper at AAAI 202

Robust Point Cloud Processing through Positional Embedding

End-to-end trained per-point embeddings are an essential ingredient of any state-of-the-art 3D point cloud processing such as detection or alignment. Methods like PointNet, or the more recent point cloud transformer -- and its variants -- all employ learned per-point embeddings. Despite impressive performance, such approaches are sensitive to out-of-distribution (OOD) noise and outliers. In this paper, we explore the role of an analytical per-point embedding based on the criterion of bandwidth. The concept of bandwidth enables us to draw connections with an alternate per-point embedding -- positional embedding, particularly random Fourier features. We present compelling robust results across downstream tasks such as point cloud classification and registration with several categories of OOD noise.Comment: 18 pages, 13 figures, 5 table

Eliciting Knowledge from Large Pre-Trained Models for Unsupervised Knowledge-Grounded Conversation

Recent advances in large-scale pre-training provide large models with the potential to learn knowledge from the raw text. It is thus natural to ask whether it is possible to leverage these large models as knowledge bases for downstream tasks. In this work, we answer the aforementioned question in unsupervised knowledge-grounded conversation. We explore various methods that best elicit knowledge from large models. Our human study indicates that, though hallucinations exist, large models post the unique advantage of being able to output common sense and summarize facts that cannot be directly retrieved from the search engine. To better exploit such generated knowledge in dialogue generation, we treat the generated knowledge as a noisy knowledge source and propose the posterior-based reweighing as well as the noisy training strategy. Empirical results on two benchmarks show advantages over the state-of-the-art methods.Comment: Accepted to EMNLP 2022 Main Conference. The code is publicly available at https://github.com/lyy1994/PLM_as_KB/tree/main/projects/plm_as_k