Pinned Repositories
concordia-game-jam-2023-nov
little-game
LittleIsland
ResCoCo-Residual-ConvLSTM-Network-with-Contrastive-Learning-for-3D-Joint-Angle-Estimation
ResCoCo is a Deep Learning approach for IMU-based 3D joint angle estimation with a sequence shortening layer to discard part of the output sequence estimated by bi-directional LSTM layers from incomplete context, a residual block for network depth increase, and contrastive learning for robust and efficient representation extraction.
little-game
LouXijian's Repositories
LouXijian/ResCoCo-Residual-ConvLSTM-Network-with-Contrastive-Learning-for-3D-Joint-Angle-Estimation
ResCoCo is a Deep Learning approach for IMU-based 3D joint angle estimation with a sequence shortening layer to discard part of the output sequence estimated by bi-directional LSTM layers from incomplete context, a residual block for network depth increase, and contrastive learning for robust and efficient representation extraction.
LouXijian/concordia-game-jam-2023-nov
LouXijian/little-game
LouXijian/LittleIsland