Search Results for author: Jiaolong Xu

Found 7 papers, 3 papers with code

Trajectory Prediction for Autonomous Driving with Topometric Map

1 code implementation9 May 2021 Jiaolong Xu, Liang Xiao, Dawei Zhao, Yiming Nie, Bin Dai

The experimental results show that the proposed method outperforms state-of-the-art multimodal methods and is robust to the perturbations of the topometric map.

Autonomous Driving Trajectory Prediction

Attentional Graph Neural Network for Parking-slot Detection

1 code implementation6 Apr 2021 Chen Min, Jiaolong Xu, Liang Xiao, Dawei Zhao, Yiming Nie, Bin Dai

Deep learning has recently demonstrated its promising performance for vision-based parking-slot detection.

Self-supervised Domain Adaptation for Computer Vision Tasks

1 code implementation25 Jul 2019 Jiaolong Xu, Liang Xiao, Antonio M. Lopez

Additionally, we propose two complementary strategies to further boost the domain adaptation accuracy on semantic segmentation within our method, consisting of prediction layer alignment and batch normalization calibration.

Domain Adaptation Object Recognition +2

Training a Binary Weight Object Detector by Knowledge Transfer for Autonomous Driving

no code implementations17 Apr 2018 Jiaolong Xu, Peng Wang, Heng Yang, Antonio M. López

Autonomous driving has harsh requirements of small model size and energy efficiency, in order to enable the embedded system to achieve real-time on-board object detection.

Autonomous Driving Object Detection +1

From Virtual to Real World Visual Perception using Domain Adaptation -- The DPM as Example

no code implementations29 Dec 2016 Antonio M. Lopez, Jiaolong Xu, Jose L. Gomez, David Vazquez, German Ros

However, since the models learned with virtual data must operate in the real world, we still need to perform domain adaptation (DA).

Domain Adaptation

Hierarchical Adaptive Structural SVM for Domain Adaptation

no code implementations22 Aug 2014 Jiaolong Xu, Sebastian Ramos, David Vazquez, Antonio M. Lopez

In both cases, we show how HA-SSVM is effective in increasing the detection/recognition accuracy with respect to adaptation strategies that ignore the structure of the target data.

Domain Adaptation General Classification +3

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