Specialized Re-Ranking: A Novel Retrieval-Verification Framework for Cloth Changing Person Re-Identification

Cloth changing person re-identification(Re-ID) can work under more complicated scenarios with higher security than normal Re-ID and biometric techniques and is therefore extremely valuable in applications. Meanwhile, higher flexibility in appearance always leads to more similar-looking confusing images, which is the weakness of the widely used retrieval methods. In this work, we shed light on how to handle these similar images. Specifically, we propose a novel retrieval-verification framework. Given an image, the retrieval module can search for similar images quickly. Our proposed verification network will then compare the input image and the candidate images by contrasting those local details and give a similarity score. An innovative ranking strategy is also introduced to take a good balance between retrieval and verification results. Comprehensive experiments are conducted to show the effectiveness of our framework and its capability in improving the state-of-the-art methods remarkably on both synthetic and realistic datasets.Comment: Accepted by Pattern Recognitio

GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

This paper aims to efficiently enable Large Language Models (LLMs) to use multimodal tools. Advanced proprietary LLMs, such as ChatGPT and GPT-4, have shown great potential for tool usage through sophisticated prompt engineering. Nevertheless, these models typically rely on prohibitive computational costs and publicly inaccessible data. To address these challenges, we propose the GPT4Tools based on self-instruct to enable open-source LLMs, such as LLaMA and OPT, to use tools. It generates an instruction-following dataset by prompting an advanced teacher with various multi-modal contexts. By using the Low-Rank Adaptation (LoRA) optimization, our approach facilitates the open-source LLMs to solve a range of visual problems, including visual comprehension and image generation. Moreover, we provide a benchmark to evaluate the ability of LLMs to use tools, which is performed in both zero-shot and fine-tuning ways. Extensive experiments demonstrate the effectiveness of our method on various language models, which not only significantly improves the accuracy of invoking seen tools, but also enables the zero-shot capacity for unseen tools. The code and demo are available at https://github.com/StevenGrove/GPT4Tools

Association Between Social Integration and Health Among Internal Migrants in ZhongShan, China

Internal migrants are the individuals who migrate between regions in one country. The number of internal migrants were estimated at 245 million in China in 2013. Results were inconsistent in the literature about the relationship between their health statuses and social integration. The main difference exists on how to measure the social integration and whether health statuses of internal migrants improve with years of residence. To complement the existing literature, this study measured social integration more comprehensively and estimated the internal migrants\u27 health statuses with varying years of residence, and explored the associations between the migrants\u27 social integration and health. We used the data from 2014 Internal Migrant Dynamic Monitoring Survey of Health and Family Planning in ZhongShan, China. Health status was measured from four aspects: self-reported health, subjective well-being, perception of stress, mental health. We measured social integration through four dimensions: economy, social communication, acculturation, and self-identity. The analyses used multiple linear regressions to examine the associations between selfreported health, subjective well-being, and perception of stress, mental health and social integration. The analytical sample included 1,999 households of the internal migrants and 1,997 local registered households, who were permanent residents in ZhongShan. Among the internal migrants, Adults in the labor force, who were aged 25 to 44 years old, accounted for 91.2% of the internal migrant population, while 74.6% of the registered population were in that age group. Median residential time among migrants was 2.8 (1.3-6.2) years, and 20.2% of them were migrating in the same Guangdong province. Except for mental health, other health statuses among migrants had significant differences compared with local registered population, e. g. self-reported health was better, but subjective well-being was worse. However, these health measurements were improved with more years of residence. Moreover, our results show that two aspects of social integration, economic integration and selfidentity, were significantly associated with health status. Subjective feeling of relative social status levels were more associated with health, which prompted the attention to social fairness and the creation of a fair and respectful culture. More interventions could be experimented, such as encouraging internal migrants to participate in community activities more actively, educating local registered residents to treat internal migrants more equally, and developing self-identity among internal migrants. Better social, economic, and cultural environment can benefit internal migrants\u27 health statuses

Prediction of natural fracture distribution characteristics in tight oil and gas reservoirs based on paleotectonic stress field

The production of fractured oil and gas reservoirs in the world accounts for more than half of total oil and gas production and is one of the important fields for increasing oil and gas storage and production in the 21st century. The key to characterizing fractured oil and gas reservoirs is the distribution pattern of natural fractures. The distribution of natural fractures is dominated by structural deformations and fractures. Therefore, analytical and structural simulations of the tectonic stress field in geological structural systems play a crucial role in obtaining fracture distribution patterns. In this paper we have developed a description of the distribution of natural fractures based on finite element numerical simulations of the paleotectonic stress field. The study focused on the Chang 7 and Huangjialing Chang 8 reservoirs in the underground Siwan region of the Ordos Basin in China. First, an experimental assessment of the rock mechanics of the reservoir was completed, and the values of the paleotectonic stresses obtained from the tests were used as inversion criteria for the stress field simulations. Based on the geology, a refined geological model has been developed to study the structure of the Chang 7 and Chang 8 oil reservoirs in the block. The simulated paleotectonic stress fields for natural fractures in the Indosinian period are as follows: maximum principal stress of 94.67 MPa, minimum principal stress of 21.58 MPa, and vertical stress of 28.07 MPa. The direction of maximum principal stress remains essentially in the NE-SW direction, with the largest differential stress occurring in the Chang 8 oil layer group in Huangjialing, while the differential stress is relatively uniform in the Chang 7 oil layer group in Xiasiwan. It predicts the relative density of natural fractures in the Chang 7 and Chang 8 reservoirs, and finds high-to-low plane heterogeneity in the Huangjialing Chang 8 reservoir group and the Xiasiwan Chang 7 reservoir group, respectively. The paper reveals the pattern of development of reservoir fractures in both vertical and horizontal directions, providing an important geological basis for efficient and rational exploitation of oil and gas resources in the study area and improving oil recovery