Point Cloud Processing via Recurrent Set Encoding

We present a new permutation-invariant network for 3D point cloud processing. Our network is composed of a recurrent set encoder and a convolutional feature aggregator. Given an unordered point set, the encoder firstly partitions its ambient space into parallel beams. Points within each beam are then modeled as a sequence and encoded into subregional geometric features by a shared recurrent neural network (RNN). The spatial layout of the beams is regular, and this allows the beam features to be further fed into an efficient 2D convolutional neural network (CNN) for hierarchical feature aggregation. Our network is effective at spatial feature learning, and competes favorably with the state-of-the-arts (SOTAs) on a number of benchmarks. Meanwhile, it is significantly more efficient compared to the SOTAs.Comment: AAAI201

Evolution of long-term ecological security pattern of island city and its influencing factors—a case study in Pingtan Island

Introduction: As the global urbanization process accelerates, the contradiction between economic development demands and ecological protection becomes increasingly prominent.Methods: In this study, we simulated the evolution of the ecological security pattern (ESP) of Pingtan Island from 2000 to 2020 by extracting the ecological sources using Remote Sensing Ecological Index (RSEI), and identifying the ecological corridors and key nodes by combining with Linkage Mapping (LM) and Circuit Theory. In addition, Geodetector was utilized to identify these major determinants affecting RSEI.Results: The results showed 1) From 2000 to 2020, the ecological environmental quality (EEQ) of Pingtan Island continued to improve, and the mean value of RSEI gradually increased from 0.47 to 0.51. 2) Univariate analysis showed that elevation and slope were the most significant factors affecting the spatial variability of the RSEI, with the interaction between slope and proportion of built-up area having a significant effect on EEQ. 3) The number and extent of ecological sources were expanded year by year with significant spatial variability. At the same time, the number and range of ecological corridors also underwent phase adjustment. 4) Further exploration of ESP of Pingtan Island in 2020 identified 32 ecological pinch points (EPPs) and 52 ecological barrier points (EBPs), which were mainly located within or near the ecological corridors, indicating key areas for future ecological restoration efforts.Discussion: These insights help to enhance urban spatial planning and ecosystem restoration on Pingtan Island and provide a blueprint for ESP development in comparable island urban environments

Becoming a backpacker in China: A grounded theory approach to identity construction of backpackers

Backpacking tourism has gained in popularity among Chinese young people since the 1990s. While learning from their western counterparts, Chinese backpackers have also developed their own unique group identification strategies. By focusing on how backpacker identity is socially constructed in the Chinese context, this research explores the meaning and process of becoming a backpacker in China. Grounded theory was adopted, and the structure “image-identity-strategy” emerged to organise the process of becoming a backpacker into three phases. The findings show that Chinese backpackers employ various strategies to continuously negotiate and reconstruct their backpacker identity. It is thereby shown how the process itself of becoming a backpacker is always ongoing

Am I a backpacker? Factors indicating the social identity of Chinese backpackers

The question of what constitutes backpacker identity has been one of the central topics of backpacking tourism research. With the economic boom in China, the last two decades witnessed the proliferation of Chinese backpackers. By adopting quantitative methods, this study provides a comprehensive understanding of what makes one a “backpacker” in China. Comparing results from t-tests, binomial logistic regression, and multiple linear regression, it is found that Chinese backpackers’ social identities are mostly associated with external-oriented motivation, work alienation, and detachment from home centers. Behavioral characteristics, which have up until now been widely used to define backpackers, have very limited relationship to their identities in China. This finding calls for future research to rethink what is a backpacker. The research makes an important contribution to the understanding of this growing market and its particular identity factors

Object-Guided Instance Segmentation for Biological Images

Instance segmentation of biological images is essential for studying object behaviors and properties. The challenges, such as clustering, occlusion, and adhesion problems of the objects, make instance segmentation a non-trivial task. Current box-free instance segmentation methods typically rely on local pixel-level information. Due to a lack of global object view, these methods are prone to over- or under-segmentation. On the contrary, the box-based instance segmentation methods incorporate object detection into the segmentation, performing better in identifying the individual instances. In this paper, we propose a new box-based instance segmentation method. Mainly, we locate the object bounding boxes from their center points. The object features are subsequently reused in the segmentation branch as a guide to separate the clustered instances within an RoI patch. Along with the instance normalization, the model is able to recover the target object distribution and suppress the distribution of neighboring attached objects. Consequently, the proposed model performs excellently in segmenting the clustered objects while retaining the target object details. The proposed method achieves state-of-the-art performances on three biological datasets: cell nuclei, plant phenotyping dataset, and neural cells.Comment: accepted to AAAI202