Search Results for author: Zhaoqi Wang

Found 8 papers, 2 papers with code

How Can I See My Future? FvTraj: Using First-person View for Pedestrian Trajectory Prediction

no code implementations ECCV 2020 Huikun Bi, Ruisi Zhang, Tianlu Mao, Zhigang Deng, Zhaoqi Wang

This work presents a novel First-person View based Trajectory predicting model (FvTraj) to estimate the future trajectories of pedestrians in a scene given their observed trajectories and the corresponding first-person view images.

Pedestrian Trajectory Prediction Trajectory Prediction

SD-MVS: Segmentation-Driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization

no code implementations12 Jan 2024 Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang, Zhaoqi Wang

In this paper, we introduce Segmentation-Driven Deformation Multi-View Stereo (SD-MVS), a method that can effectively tackle challenges in 3D reconstruction of textureless areas.

3D Reconstruction

EANet: Expert Attention Network for Online Trajectory Prediction

no code implementations11 Sep 2023 Pengfei Yao, Tianlu Mao, Min Shi, Jingkai Sun, Zhaoqi Wang

We introduce expert attention, which adjusts the weights of different depths of network layers, avoiding the model updated slowly due to gradient problem and enabling fast learning of new scenario's knowledge to restore prediction accuracy.

Autonomous Driving Trajectory Prediction

Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo

no code implementations19 Aug 2023 Zhenlong Yuan, Jiakai Cao, Hao Jiang, Zhaoqi Wang, Zhaoxin Li

The reconstruction of textureless areas has long been a challenging problem in MVS due to lack of reliable pixel correspondences between images.

3D Reconstruction Edge Detection +3

Radiative Transport Based Flame Volume Reconstruction from Videos

no code implementations17 Sep 2018 Liang Shen, Dengming Zhu, Saad Nadeem, Zhaoqi Wang, Arie Kaufman

The approach includes an economical data capture technique using inexpensive CCD cameras.

Simulation assisted machine learning

1 code implementation15 Feb 2018 Timo M. Deist, Andrew Patti, Zhaoqi Wang, David Krane, Taylor Sorenson, David Craft

When sufficient system details are not known, one typically turns to machine learning, which builds a black-box model of the system using a large dataset of input sample features and outputs.

BIG-bench Machine Learning

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