Papers with Code 아카이브
NLP based Person Retrival
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MysteryVaibhav/DW-GAE
https://github.com/MysteryVaibhav/LAS
https://github.com/NLP-Discourse-SoochowU/t2d_discourseparser
A Top-Down Neural Architecture towards Text-Level Parsing of Discourse Rhetorical Structure
https://github.com/NSR9/DenseDepth
High Quality Monocular Depth Estimation via Transfer Learning
https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Translation/GNMT
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
https://github.com/NVIDIA/MinkowskiEngine
Generative Sparse Detection Networks for 3D Single-shot Object Detection
https://github.com/NVIDIA/NeMo
Stateful Conformer with Cache-based Inference for Streaming Automatic Speech Recognition
https://github.com/NVIDIA/OpenSeq2Seq
https://github.com/NVIDIA/sentiment-discovery
https://github.com/NVlabs/Sana
SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers
https://github.com/NVlabs/sionna/blob/main/examples/Weighted_BP_Algorithm.ipynb
https://github.com/Navhkrin/Bts-PyTorch
From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation
https://github.com/Neoanarika/torchexplainer
https://github.com/Net-Mist/style-transfer-tf2
https://github.com/NeurIps2239/ExtraMAE
https://github.com/NeuronDroid/GVSS-S.A.Drone
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/NiallEHunt/MonocularDepth-Using-LightFields
High Quality Monocular Depth Estimation via Transfer Learning
https://github.com/Nick-Zhao-Engr/Machine-Translation
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://github.com/Niharika-SD/Matrix-Autoencoder
https://github.com/NikV-JS/U-Det
U-Det: A Modified U-Net architecture with bidirectional feature network for lung nodule segmentation
https://github.com/Nikolai10/MRIC
Multi-Realism Image Compression with a Conditional Generator
https://github.com/Nikolai10/SwinT-ChARM
EGIC: Enhanced Low-Bit-Rate Generative Image Compression Guided by Semantic Segmentation
https://github.com/Nimesh-Patel/BERT
https://github.com/Nirvanabc/seq2seq-rnn
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
https://github.com/NoaCahan/WavenetAutoEncoder
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders
https://github.com/Noopuragr/DepthModel
High Quality Monocular Depth Estimation via Transfer Learning
https://github.com/Nstats/bert_MRC
https://github.com/Nstats/bert_senti_analysis_ch
https://github.com/Nstats/my_bert
https://github.com/Nullius-2020/MAE-Paddle
https://github.com/OPAYA/Transformer
https://github.com/Oguzhanercan/Vision-Transformers
https://github.com/Omairss/RepresentationLearning
https://github.com/OneYearIsEnough/PaddleOCR-Recog-LmdbDataset-Conversion
Primitive Representation Learning for Scene Text Recognition
https://github.com/OniroAI/Instance-segmentation-with-MobileNetV3
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.