Papers with Code 아카이브
NLP based Person Retrival
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://gitlab.com/codegenfact/BertranX
공식 코드The impact of lexical and grammatical processing on generating code from natural language
https://gitlab.com/codegenfactors/BertranX
공식 코드The impact of lexical and grammatical processing on generating code from natural language
https://gitlab.com/csltstu/sunine
공식 코드The NPU-ASLP System Description for Visual Speech Recognition in CNVSRC 2024
https://gitlab.com/hzxie/Pix2Vox
공식 코드Pix2Vox++: Multi-scale Context-aware 3D Object Reconstruction from Single and Multiple Images
https://gitlab.com/jubrau/lbd
공식 코드Convergent autoencoder approximation of low bending and low distortion manifold embeddings
https://gitlab.com/matzkin/deep-brain-extractor
공식 코드Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy
https://huggingface.co/ibm/materials.smi-ted
공식 코드A Large Encoder-Decoder Family of Foundation Models For Chemical Language
https://renkulab.io/gitlab/bistom/enca-inca
공식 코드Learning Summary Statistics for Bayesian Inference with Autoencoders
https://dagshub.com/Bharat-mtr/One_Shot_Face_Reenactment
https://git.zib.de/ableich/ecg-comment-generation-public
https://gitee.com/HarveyYeung/BCS-Net-MindSpore.git
https://github.com/04RR/SOTA-Vision
https://github.com/0bserver07/Keras-SegNet-Basic
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/0jason000/mae_vit
https://github.com/1wy/bert
https://github.com/1zb/pytorch-image-comp-rnn
Full Resolution Image Compression with Recurrent Neural Networks
https://github.com/20000607-lxc/TransformerCVAE-master
Transformer-based Conditional Variational Autoencoder for Controllable Story Generation
https://github.com/2020132075/conmae
https://github.com/2023-MindSpore-1/ms-code-114
Omni-supervised Point Cloud Segmentation via Gradual Receptive Field Component Reasoning
https://github.com/2023-MindSpore-1/ms-code-118
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-14
CIR-Net: Cross-modality Interaction and Refinement for RGB-D Salient Object Detection
https://github.com/2023-MindSpore-1/ms-code-14/tree/main/GRU
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://github.com/2023-MindSpore-1/ms-code-14/tree/main/Transformer
https://github.com/2023-MindSpore-1/ms-code-147
CIR-Net: Cross-modality Interaction and Refinement for RGB-D Salient Object Detection
https://github.com/2023-MindSpore-1/ms-code-149
https://github.com/2023-MindSpore-1/ms-code-15
https://github.com/2023-MindSpore-1/ms-code-15/tree/main/FastSpeech
https://github.com/2023-MindSpore-1/ms-code-15/tree/main/jasper
https://github.com/2023-MindSpore-1/ms-code-15/tree/main/speech_transformer
A Simplified Fully Quantized Transformer for End-to-end Speech Recognition
https://github.com/2023-MindSpore-1/ms-code-155
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/AdaBin
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/AttGAN
AttGAN: Facial Attribute Editing by Only Changing What You Want
https://github.com/2023-MindSpore-1/ms-code-161
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/lenet
LENet: Lightweight And Efficient LiDAR Semantic Segmentation Using Multi-Scale Convolution Attention
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/m2det
M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.