Repulsion Loss: Detecting Pedestrians in a Crowd

Detecting individual pedestrians in a crowd remains a challenging problem since the pedestrians often gather together and occlude each other in real-world scenarios. In this paper, we first explore how a state-of-the-art pedestrian detector is harmed by crowd occlusion via experimentation, providing insights into the crowd occlusion problem. Then, we propose a novel bounding box regression loss specifically designed for crowd scenes, termed repulsion loss. This loss is driven by two motivations: the attraction by target, and the repulsion by other surrounding objects. The repulsion term prevents the proposal from shifting to surrounding objects thus leading to more crowd-robust localization. Our detector trained by repulsion loss outperforms all the state-of-the-art methods with a significant improvement in occlusion cases.Comment: Accepted to IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 201

Aseismic Study on Mountain Tunnels in High-Intensity Seismic Area

The chapter discusses the antiseismic and shock absorption study on the mountain tunnels in high-seismic intensity areas using numerical analysis and shaking table test for recent years and proposes the seismic challenges of tunnel design in Sichuan-Tibet Railway. The aseismic design of the tunnel entrance and the inner part in the fracture zone are presented according to the previous research results

A state-space based method to predict thermal performance of pipeembedded double skin façade: case study in Guangzhou

Pipe-embedded double skin facade, which arranges pipes in shading device, is an alternative to reduce indoor demand and save energy. To simulate annual performance of this system, a simplified approach based on optical and thermal property is proposed at first, in which dynamic performance is acquired through state-space method. Then the model is validated with former investigation and shows good accuracy. Indoor room temperature with the pipe-embedded double skin façade is analyzed under different types of room in Guangzhou at last. Results show that the pipe-embedded double skin façade could guarantee a barely satisfactory indoor environment where indoor heat gain is small in most time. Besides, superiority would be obvious when solar radiation is strong, indicating the applicability in some typical region with abundant sunshine

InfeRE: Step-by-Step Regex Generation via Chain of Inference

Automatically generating regular expressions (abbrev. regexes) from natural language description (NL2RE) has been an emerging research area. Prior studies treat regex as a linear sequence of tokens and generate the final expressions autoregressively in a single pass. They did not take into account the step-by-step internal text-matching processes behind the final results. This significantly hinders the efficacy and interpretability of regex generation by neural language models. In this paper, we propose a new paradigm called InfeRE, which decomposes the generation of regexes into chains of step-by-step inference. To enhance the robustness, we introduce a self-consistency decoding mechanism that ensembles multiple outputs sampled from different models. We evaluate InfeRE on two publicly available datasets, NL-RX-Turk and KB13, and compare the results with state-of-the-art approaches and the popular tree-based generation approach TRANX. Experimental results show that InfeRE substantially outperforms previous baselines, yielding 16.3% and 14.7% improvement in DFA@5 accuracy on two datasets, respectively. Particularly, InfeRE outperforms the popular tree-based generation approach by 18.1% and 11.3% on both datasets, respectively, in terms of DFA@5 accuracy.Comment: This paper has been accepted by ASE'2

Research on the Movement Law of Gravel under Water Based on the Principle of Audio Analysis

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive