Official PyTorch implementation of "I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB Image", ECCV 2020
Hi!
Thanks for your excellent work!
I have some quetions on freihand_train_data.json format.In the training_mano.json annotation file provided with the Freihand dataset, the first 48 denote poses, 49-58 are shapes, and the last three are trans; in your freihand_train_data.json file, the mano_param is divided into pose, shape, and trans, where the shape part is the same as the shape part provided in the Freihand dataset, but the pose and trans parts are different, can you tell me what transformations are done?
Hi! Thanks for your excellent work! I have some quetions on freihand_train_data.json format.In the training_mano.json annotation file provided with the Freihand dataset, the first 48 denote poses, 49-58 are shapes, and the last three are trans; in your freihand_train_data.json file, the mano_param is divided into pose, shape, and trans, where the shape part is the same as the shape part provided in the Freihand dataset, but the pose and trans parts are different, can you tell me what transformations are done?