08 2021 档案

How Graph Neural Networks (GNN) work: introduction to graph convolutions from scratch
摘要：https://theaisummer.com/graph-convolutional-networks/ 阅读全文
posted @ 2021-08-20 17:40 郭新晨 阅读(23) 评论(0) 推荐(0) 编辑
Multi-Class Social STGCNN
摘要：https://github.com/brainbow30/Multi-Class-Social-STGCNN 阅读全文
posted @ 2021-08-19 14:22 郭新晨 阅读(18) 评论(0) 推荐(0) 编辑
About Building on the work of Social STGCNN we introduce Multi-Class Social STGCNN to include class information into trajectory prediction to improve the accuracy.
摘要：https://github.com/Yutasq/Multi-Class-Social-STGCNN 阅读全文
posted @ 2021-08-19 14:20 郭新晨 阅读(11) 评论(0) 推荐(0) 编辑
pytorch whl
摘要：https://download.pytorch.org/whl/torch_stable.html 阅读全文
posted @ 2021-08-19 10:07 郭新晨 阅读(41) 评论(0) 推荐(0) 编辑
About Building on the work of Social STGCNN we introduce Multi-Class Social STGCNN to include class information into trajectory prediction to improve the accuracy
摘要：https://github.55860.com/brainbow30/Multi-Class-Social-STGCNN 阅读全文
posted @ 2021-08-18 18:44 郭新晨 阅读(14) 评论(0) 推荐(0) 编辑
Social-STGCNN：CVPR2020论文翻译以及解读
摘要：https://blog.csdn.net/qq_41897558/article/details/104774320 阅读全文
posted @ 2021-08-18 17:59 郭新晨 阅读(179) 评论(0) 推荐(0) 编辑
CVPR2020行人轨迹预测论文Social-STGCNN
摘要：https://zhuanlan.zhihu.com/p/268950854 阅读全文
posted @ 2021-08-18 17:56 郭新晨 阅读(227) 评论(0) 推荐(0) 编辑
Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch
摘要：https://github.com/yysijie/st-gcn 阅读全文
posted @ 2021-08-18 17:50 郭新晨 阅读(32) 评论(0) 推荐(0) 编辑
CrowdNav with Social-NCE
摘要：https://github.com/vita-epfl/social-nce-crowdnav 阅读全文
posted @ 2021-08-05 15:30 郭新晨 阅读(33) 评论(0) 推荐(0) 编辑
Official implementation of the "Social NCE: Contrastive Learning of Socially-aware Motion Representations" in PyTorch,
摘要：https://github.com/qiyan98/social-nce-stgcnn 阅读全文
posted @ 2021-08-05 15:28 郭新晨 阅读(25) 评论(0) 推荐(0) 编辑
PyTorch implementation of the Social-NCE applied to Trajectron++.
摘要：https://github.com/YuejiangLIU/social-nce-trajectron-plus-plus 阅读全文
posted @ 2021-08-05 15:27 郭新晨 阅读(25) 评论(0) 推荐(0) 编辑
Code accompanying the ECCV 2020 paper "Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data"
摘要：https://github.com/StanfordASL/Trajectron-plus-plus 阅读全文
posted @ 2021-08-05 15:25 郭新晨 阅读(76) 评论(0) 推荐(0) 编辑
AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting
摘要：https://www.ye-yuan.com/agentformer/ 阅读全文
posted @ 2021-08-03 11:19 郭新晨 阅读(206) 评论(0) 推荐(0) 编辑
Trajectory Prediction
摘要：https://paperswithcode.com/task/trajectory-prediction 阅读全文
posted @ 2021-08-03 11:11 郭新晨 阅读(59) 评论(0) 推荐(0) 编辑
It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Prediction
摘要：https://karttikeya.github.io/publication/htf/ 阅读全文
posted @ 2021-08-03 11:10 郭新晨 阅读(22) 评论(0) 推荐(0) 编辑

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