| Year | Name | Arxiv | CODE |
|---|---|---|---|
| 2016 | BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding |   |
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| 2023 | ChatLaw: Open-Source Legal Large Language Model with Integrated External Knowledge Bases | |
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| 2023 | GPT-4 Technical Report | |
| Year | Name | Arxiv | CODE |
|---|---|---|---|
| 2013 | R-CNN: Rich feature hierarchies for accurate object detection and semantic segmentation | |
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| 2015 | Style Transfer: A Neural Algorithm of Artistic Style | |
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| 2016 | DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs | |
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| 2016 | Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks | |
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| 2016 | SegNet: A Deep Convolutional Encoder-Decoder Architecture for image segmentation | |
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| 2017 | Mask R-CNN: Rich feature hierarchies for accurate object detection and semantic segmentation | |
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| 2020 | FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping | |
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| 2020 | Cycle GAN :Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks | |
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| 2020 | A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wild | |
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| 2020 | NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis | |
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| 2021 | AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis | |
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| 2022 | High-Resolution Image Synthesis with Latent Diffusion Models | |
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| 2022 | StyleSwap: Style-Based Generator Empowers Robust Face Swapping | |
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| 2022 | Few-Shot Head Swapping in the Wild | |
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| 2022 | MobileFaceSwap: A Lightweight Framework for Video Face Swapping | |
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| 2022 | Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis | |
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| 2022 | StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pretrained StyleGAN | |
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| 2022 | Multi-View Consistent Generative Adversarial Networks for 3D-aware Image Synthesis | |
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| 2022 | FNeVR: Neural Volume Rendering for Face Animation | |
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| 2022 | EpiGRAF: Rethinking training of 3D GANs | |
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| 2023 | Text-To-4D Dynamic Scene Generation | |
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| 2023 | StyleTalk: One-shot Talking Head Generation with Controllable Speaking Styles | |
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| 2023 | Efficient Region-Aware Neural Radiance Fields for High-Fidelity Talking Portrait Synthesis | |
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| 2023 | DINet: Deformation Inpainting Network for Realistic Face Visually Dubbing on High-Resolution Video | |
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| 2023 | DiffusionVideoEditing: Speech Driven Video Editing via an Audio-Conditioned Diffusion Model | |
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| 2023 | Implicit Identity Representation Conditioned Memory Compensation Network for Talking Head Video Generation | |
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| 2023 | OTAvatar : One-shot Talking Face Avatar with Controllable Tri-plane Rendering | |
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| 2023 | Seeing What You Said: Talking Face Generation Guided by a Lip Reading Expert | |
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| 2023 | GeneFace: Generalized and High-Fidelity Audio-Driven 3D Talking Face Synthesis | |
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| 2023 | CodeTalker: Speech-Driven 3D Facial Animation with Discrete Motion Prior | |
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| 2023 | Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatars | |
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| 2023 | Conditional Image-to-Video Generation with Latent Flow Diffusion Models | |
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| 2023 | Class-consistent and Diverse Image Generation through StyleGANs | |
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| 2023 | An efficient PyTorch-based library for training 3D-aware image synthesis models. | |
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| 2023 | Semantic-aware Generation of Multi-view Portrait Drawings (SAGE) | |
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| 2023 | Single-Stage Diffusion NeRF: A Unified Approach to 3D Generation and Reconstruction | |
| Year | Name | Arxiv | CODE |
|---|---|---|---|
| 2015 | U-Net: Convolutional Networks for Biomedical Image Segmentation | |
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| 2016 | 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation | |
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| 2018 | UNet++: A Nested U-Net Architecture for Medical Image Segmentation |  |
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| 2019 | UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation | |
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| 2018 | nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation | |
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| 2018 | LadderNet: Multi-path networks based on U-Net for medical image segmentation | |
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| 2018 | R2U-Net : Recurrent Residual Convolutional Neural Network based on U-Net for Medical Image Segmentation | |
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| 2018 | Attention U-Net : Learning Where to Look for the Pancreas | |
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| 2019 | MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation | |
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| 2019 | ResUNet++: An Advanced Architecture for Medical Image Segmentation | |
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| 2020 | UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation | |
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| 2020 | DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation | |
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| 2020 | DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmentation | |
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| 2020 | CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation | |
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| 2020 | SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation | |
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| 2021 | TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation | |
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| 2021 | U-Net Transformer: Self and Cross Attention for Medical Image Segmentation | |
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| 2021 | Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation | |
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| 2021 | UTNet : A Hybrid Transformer Architecture for Medical Image Segmentation | |
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| 2021 | UNETR: Transformers for 3D Medical Image Segmentation | |
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| 2021 | PocketNet: A Smaller Neural Network for Medical Image Analysis | |
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| 2021 | UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation | |
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| 2022 | 3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation | |
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| 2022 | Contextual Attention Network: Transformer Meets U-Net | |
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| 2022 | UNeXt: MLP-based Rapid Medical Image Segmentation Network | |
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| 2022 | The Fully Convolutional Transformer for Medical Image Segmentation | |
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| 2023 | MaxViT-UNet: Multi-Axis Attention for Medical Image Segmentation | |
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| 2023 | CMUNeXt: An Efficient Medical Image Segmentation Network based on Large Kernel and Skip Fusion | |
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| 2023 | SAM-Med2D | |
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| 2023 | Segment Anything Model for Medical Image Analysis: an Experimental Study | |
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| 2023 | ScaleCrafter for higher-resolution visual generation at inference time | |