3DHumanGAN
A 3D-aware generative adversarial network (GAN) that synthesizes images of full-body humans with consistent appearances under different view-angles and body-poses.
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최종 버전 다운로드 (.zip)- sample_from_generator.py
- train.py
- teaser.jpg
- __init__.py
- map3d.py
- densepose_data.json
- ACKNOWLEDGEMENT.md
- GET_STARTED.md
- INSTALL.md
- __init__.py
- bias_act.cpp
- bias_act.cu
- bias_act.h
- bias_act.py
- conv2d_gradfix.py
- conv2d_resample.py
- filtered_lrelu.cpp
- filtered_lrelu.cu
- filtered_lrelu.h
- filtered_lrelu.py
- filtered_lrelu_ns.cu
- filtered_lrelu_rd.cu
- filtered_lrelu_wr.cu
- fma.py
- fused_act.py
- fused_bias_act.cpp
- fused_bias_act_kernel.cu
- grid_sample_gradfix.py
- upfirdn2d.cpp
- upfirdn2d.cu
- upfirdn2d.h
- upfirdn2d.py
- __init__.py
- cips_layers.py
- custom_ops.py
- ema.py
- map3d_layers.py
- mapping_networks.py
- nv_misc.py
- perceptual_loss.py
- persistence.py
- pigan_layers.py
- smpl.py
- training_stats.py
- util.py
- __init__.py
- augment.py
- datasets.py
- preprocessor.py
- utils.py
- __init__.py
- unet_discriminators.py
- __init__.py
- map3d_generator.py
- volume_rendering.py
- __init__.py
- modulated.py
- __init__.py
- base_trainer.py
- phase_trainer.py
- __init__.py
- README.md
// repository documentation
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