In this article, we explored the Social LSTM model for predicting the future trajectories of surrounding vehicles. We implemented the model using PyTorch and demonstrated how to train it on vehicle data. The Social LSTM model is a powerful tool in the development of autonomous vehicles and can s...
在每个时间,LSTM小区从邻居的LSTM接收合并的隐藏状态信息,在汇集信息时,我们尝试通过基于网格的池化来保留空间信息。 LSTM 在时间 t 捕获那个瞬间场景中第 i 个人的潜在表征为隐藏状态h_{i}^{t}。我们加入一个 Social Pooling层来共享邻近的信息,构建了一个N_{0}\times N_{0}\times D张量(两个维度是平面坐...
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Social LSTM: Human Trajectory Prediction in Crowded Spaces论文解读论文地址: https://openaccess.thecvf.com/content_cvpr_2016/papers/Alahi_Social_LSTM_Human_CVPR_2016_paper.pdf code(pytorch): https:/…
Social LSTM using PyTorch for Vehicle Data https://github.com/EmreTaha/Social-LSTM-VehicleTrajectory
Social LSTM implementation in PyTorch. Contribute to SHEN-zc98/social-lstm development by creating an account on GitHub.
Social LSTM implementation in PyTorch https://github.com/quancore/social-lstm 好文要顶 关注我 收藏该文 微信分享 郭新晨 粉丝- 9 关注- 1+加关注 0 0 升级成为会员 « 上一篇: PyTorch implementation of the Social LSTM model » 下一篇: Social LSTM using PyTorch for Vehicle Data ...
是否有开源代码:有 (https://github.com/J-zin/CANE-pytorch)TransNet: Translation-Based Network Representation Learning for Social Relation Extraction作者: Cunchao Tu, et al.(THUNLP) 发表时间:2017 发表于:IJCAI 2017 标签:Social Relation Extraction, Auto Encoder, Traslation Learning 概述:关注到社交网络...
The proposed model is implemented in the Pytorch framework, which employs the BERT model as the text encoder and the ViT model as the image encoder. Both models have 12 transformer layers and a hidden size of 768. It is well established in the literature that the performance of the model ...
近日在阅读Social GAN文献的实验代码,加深对模型的理解,发现源代码的工程化很强,也比较适合构建实验模型的学习,故细致阅读。下文是笔者阅读中一些要点总结,有关于pytorch,也有关于模型自身的。 GPU -> CPU SGAN的实验代码在工程化方面考虑比较充分,考虑到了在CPU和GPU两种平台上模型的运行。原生平台是GPU,若要切换为...