Search Results for author: Peng Yin

Found 20 papers, 5 papers with code

360FusionNeRF: Panoramic Neural Radiance Fields with Joint Guidance

1 code implementation28 Sep 2022 Shreyas Kulkarni, Peng Yin, Sebastian Scherer

Additionally, we introduce a semantic consistency loss that encourages realistic renderings of novel views.

SSIM

MUI-TARE: Multi-Agent Cooperative Exploration with Unknown Initial Position

no code implementations22 Sep 2022 Jingtian Yan, Xingqiao Lin, Zhongqiang Ren, Shiqi Zhao, Jieqiong Yu, Chao Cao, Peng Yin, Ji Zhang, Sebastian Scherer

To intelligently balance the robustness of sub-map merging and exploration efficiency, we develop a new approach for lidar-based multi-agent exploration, which can direct one agent to repeat another agent's trajectory in an \emph{adaptive} manner based on the quality indicator of the sub-map merging process.

Position

iSimLoc: Visual Global Localization for Previously Unseen Environments with Simulated Images

no code implementations14 Sep 2022 Peng Yin, Ivan Cisneros, Ji Zhang, Howie Choset, Sebastian Scherer

The visual camera is an attractive device in beyond visual line of sight (B-VLOS) drone operation, since they are low in size, weight, power, and cost, and can provide redundant modality to GPS failures.

Retrieval Visual Localization

BioSLAM: A Bio-inspired Lifelong Memory System for General Place Recognition

no code implementations30 Aug 2022 Peng Yin, Abulikemu Abuduweili, Shiqi Zhao, Changliu Liu, Sebastian Scherer

We present BioSLAM, a lifelong SLAM framework for learning various new appearances incrementally and maintaining accurate place recognition for previously visited areas.

Bridging the gap between target-based and cell-based drug discovery with a graph generative multi-task model

no code implementations9 Aug 2022 Fan Hu, Dongqi Wang, Huazhen Huang, Yishen Hu, Peng Yin

Based on these findings, we utilized a monte carlo based reinforcement learning generative model to generate novel multi-property compounds with both in vitro and in vivo efficacy, thus bridging the gap between target-based and cell-based drug discovery.

Drug Discovery

ALTO: A Large-Scale Dataset for UAV Visual Place Recognition and Localization

1 code implementation19 Jul 2022 Ivan Cisneros, Peng Yin, Ji Zhang, Howie Choset, Sebastian Scherer

We present the ALTO dataset, a vision-focused dataset for the development and benchmarking of Visual Place Recognition and Localization methods for Unmanned Aerial Vehicles.

Benchmarking Image Registration +2

AutoMerge: A Framework for Map Assembling and Smoothing in City-scale Environments

no code implementations14 Jul 2022 Peng Yin, Haowen Lai, Shiqi Zhao, Ruohai Ge, Ji Zhang, Howie Choset, Sebastian Scherer

We present AutoMerge, a LiDAR data processing framework for assembling a large number of map segments into a complete map.

Loop Closure Detection Retrieval

SphereVLAD++: Attention-based and Signal-enhanced Viewpoint Invariant Descriptor

no code implementations6 Jul 2022 Shiqi Zhao, Peng Yin, Ge Yi, Sebastian Scherer

Our previous work provides a viewpoint-invariant descriptor to deal with viewpoint differences; however, the global descriptor suffers from a low signal-noise ratio in unsupervised clustering, reducing the distinguishable feature extraction ability.

3D Place Recognition Autonomous Driving +1

AdaFusion: Visual-LiDAR Fusion with Adaptive Weights for Place Recognition

no code implementations23 Nov 2021 Haowen Lai, Peng Yin, Sebastian Scherer

Recent years have witnessed the increasing application of place recognition in various environments, such as city roads, large buildings, and a mix of indoor and outdoor places.

Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR

2 code implementations20 Sep 2021 Ziyue Feng, Longlong Jing, Peng Yin, YingLi Tian, Bing Li

Unlike the existing methods that use sparse LiDAR mainly in a manner of time-consuming iterative post-processing, our model fuses monocular image features and sparse LiDAR features to predict initial depth maps.

Depth Completion Depth Prediction +3

PSE-Match: A Viewpoint-free Place Recognition Method with Parallel Semantic Embedding

no code implementations1 Aug 2021 Peng Yin, Lingyun Xu, Ziyue Feng, Anton Egorov, Bing Li

Accurate localization on autonomous driving cars is essential for autonomy and driving safety, especially for complex urban streets and search-and-rescue subterranean environments where high-accurate GPS is not available.

Autonomous Driving Retrieval

3D Segmentation Learning from Sparse Annotations and Hierarchical Descriptors

no code implementations27 May 2021 Peng Yin, Lingyun Xu, Jianmin Ji, Sebastian Scherer, Howie Choset

One of the main obstacles to 3D semantic segmentation is the significant amount of endeavor required to generate expensive point-wise annotations for fully supervised training.

3D Semantic Segmentation Segmentation

Prediction of Potential Commercially Available Inhibitors against SARS-CoV-2 by Multi-Task Deep Learning Model

no code implementations2 Mar 2020 Fan Hu, Jiaxin Jiang, Peng Yin

Then, the fine-tuned model was used to select commercially available drugs against SARS-CoV-2 protein targets.

Molecular Docking

MRS-VPR: a multi-resolution sampling based global visual place recognition method

no code implementations26 Feb 2019 Peng Yin, Rangaprasad Arun Srivatsan, Yin Chen, Xueqian Li, Hongda Zhang, Lingyun Xu, Lu Li, Zhenzhong Jia, Jianmin Ji, Yuqing He

We propose MRS-VPR, a multi-resolution, sampling-based place recognition method, which can significantly improve the matching efficiency and accuracy in sequential matching.

Loop Closure Detection Visual Navigation +1

A Multi-Domain Feature Learning Method for Visual Place Recognition

no code implementations26 Feb 2019 Peng Yin, Lingyun Xu, Xueqian Li, Chen Yin, Yingli Li, Rangaprasad Arun Srivatsan, Lu Li, Jianmin Ji, Yuqing He

Visual Place Recognition (VPR) is an important component in both computer vision and robotics applications, thanks to its ability to determine whether a place has been visited and where specifically.

Attribute Visual Place Recognition

LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis

2 code implementations ICCV 2019 Zhe Liu, Shunbo Zhou, Chuanzhe Suo, Yingtian Liu, Peng Yin, Hesheng Wang, Yun-hui Liu

Point cloud based place recognition is still an open issue due to the difficulty in extracting local features from the raw 3D point cloud and generating the global descriptor, and it's even harder in the large-scale dynamic environments.

3D Place Recognition Point Cloud Retrieval +1

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