Xi'an Jiaotong University

About: Xi'an Jiaotong University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Heat transfer & Dielectric. The organization has 85440 authors who have published 99682 publications receiving 1579683 citations. The organization is also known as: '''Xi'an Jiaotong University''' & Xi'an Jiao Tong University.

A Strong Baseline and Batch Normalization Neck for Deep Person Re-Identification

Abstract: This study proposes a simple but strong baseline for deep person re-identification (ReID). Deep person ReID has achieved great progress and high performance in recent years. However, many state-of-the-art methods design complex network structures and concatenate multi-branch features. In the literature, some effective training tricks briefly appear in several papers or source codes. The present study collects and evaluates these effective training tricks in person ReID. By combining these tricks, the model achieves 94.5% rank-1 and 85.9% mean average precision on Market1501 with only using the global features of ResNet50. The performance surpasses all existing global- and part-based baselines in person ReID. We propose a novel neck structure named as batch normalization neck (BNNeck). BNNeck adds a batch normalization layer after global pooling layer to separate metric and classification losses into two different feature spaces because we observe they are inconsistent in one embedding space. Extended experiments show that BNNeck can boost the baseline, and our baseline can improve the performance of existing state-of-the-art methods. Our codes and models are available at: https://github.com/michuanhaohao/reid-strong-baseline

Corey: an operating system for many cores

Abstract: Multiprocessor application performance can be limited by the operating system when the application uses the operating system frequently and the operating system services use data structures shared and modified by multiple processing cores If the application does not need the sharing, then the operating system will become an unnecessary bottleneck to the application's performanceThis paper argues that applications should control sharing: the kernel should arrange each data structure so that only a single processor need update it, unless directed otherwise by the application Guided by this design principle, this paper proposes three operating system abstractions (address ranges, kernel cores, and shares) that allow applications to control inter-core sharing and to take advantage of the likely abundance of cores by dedicating cores to specific operating system functionsMeasurements of microbenchmarks on the Corey prototype operating system, which embodies the new abstractions, show how control over sharing can improve performance Application benchmarks, using MapReduce and a Web server, show that the improvements can be significant for overall performance: MapReduce on Corey performs 25% faster than on Linux when using 16 cores Hardware event counters confirm that these improvements are due to avoiding operations that are expensive on multicore machines