Search Results for author: Jianwei Feng

Found 6 papers, 3 papers with code

3D Face Style Transfer with a Hybrid Solution of NeRF and Mesh Rasterization

no code implementations22 Nov 2023 Jianwei Feng, Prateek Singhal

We therefore propose a hybrid framework of NeRF and mesh rasterization to combine the benefits of high fidelity geometry reconstruction of NeRF and fast rendering speed of mesh.

Style Transfer

Joint Activity Recognition and Indoor Localization With WiFi Fingerprints

1 code implementation arXiv:1904.04964 Search... Help | Advanced Search 2019 Fei Wang, Jianwei Feng, Yinliang Zhao, Xiaobin Zhang, Shiyuan Zhang, Jinsong Han

In this paper, we propose a novel deep learning framework for joint activity recognition and indoor localization task using WiFi Channel State Information~(CSI) fingerprints.

Activity Recognition Indoor Localization +1

Cutting Down Training Memory by Re-fowarding

no code implementations ICLR 2019 Jianwei Feng, Dong Huang

Our approach automatically finds a subset of vertices in a DNN computation graph, and stores tensors only at these vertices during the first forward.

Joint Activity Recognition and Indoor Localization

2 code implementations10 Apr 2019 Fei Wang, Jianwei Feng, Yinliang Zhao, Xiaobin Zhang, Shiyuan Zhang, Jinsong Han

The key rationale behind this type of work is that people behaviors can influence the WiFi signal propagation and introduce specific patterns into WiFi signals, called WiFi fingerprints, which further can be explored to identify human activities and locations.

Human-Computer Interaction

Adaptive Semantic Segmentation with a Strategic Curriculum of Proxy Labels

no code implementations8 Nov 2018 Kashyap Chitta, Jianwei Feng, Martial Hebert

With our design, the network progressively learns features specific to the target domain using annotation from only the source domain.

Semantic Segmentation Unsupervised Domain Adaptation

Optimal Gradient Checkpoint Search for Arbitrary Computation Graphs

1 code implementation CVPR 2021 Jianwei Feng, Dong Huang

In this paper, we present theories and optimal algorithms on GC selection that, for the first time, are applicable to ACGs and achieve the maximal memory cut-offs.

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