awesome-ml-papers
Awesome Machine Learning Papers
https://github.com/alan-minchan-kim/awesome-ml-papers
Last synced: 6 days ago
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CNN
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RNN
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Transformer
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AE
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GAN
- Generative Adversarial Networks
- Progressive Growing of GANs for Improved Quality, Stability, and Variation
- A Style-Based Generator Architecture for Generative Adversarial Networks
- Analyzing and Improving the Image Quality of StyleGAN
- Training Generative Adversarial Networks with Limited Data
- Alias-Free Generative Adversarial Networks
- StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2
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Flow
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Diffusion
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3DMM
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NeRF
- NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
- Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
- Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis
- Point-NeRF: Point-based Neural Radiance Fields
- A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose
- StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generation
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Normalization
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Representation Learning
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Contrastive Learning
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INR
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SR
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Face Recognition
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Facial Editting
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Talking Head
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Face Swapping
- SimSwap: An Efficient Framework For High Fidelity Face Swapping
- HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping
- FaceInpainter: High Fidelity Face Adaptation to Heterogeneous Domains
- One Shot Face Swapping on Megapixels
- ShapeEditer: a StyleGAN Encoder for Face Swapping
- FaceController: Controllable Attribute Editing for Face in the Wild
- High-Resolution Neural Face Swapping for Visual Effects
- FSGAN: Subject Agnostic Face Swapping and Reenactment
- FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
- Towards Open-Set Identity Preserving Face Synthesis
- RSGAN: Face Swapping and Editing using Face and Hair Representation in Latent Spaces
- FSNet: An Identity-Aware Generative Model for Image-based Face Swapping
- DeepFaceLab: Integrated, flexible and extensible face-swapping framework
- Deepfakes for Medical Video De-Identification: Privacy Protection and Diagnostic Information Preservation
- On Face Segmentation, Face Swapping, and Face Perception
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Background Editting
Programming Languages
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