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/2023-MindSpore-1/ms-code-197
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://github.com/2023-MindSpore-1/ms-code-200
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/2023-MindSpore-1/ms-code-206
https://github.com/2023-MindSpore-1/ms-code-211/tree/main/dnet_nas
D-Net: Siamese based Network with Mutual Attention for Volume Alignment
https://github.com/2023-MindSpore-1/ms-code-211/tree/main/dpn
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/fastflow
FastFlowNet: A Lightweight Network for Fast Optical Flow Estimation
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/fastscnn
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/IndexNet
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/REDNet30
RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/rbpn
Recurrent Back-Projection Network for Video Super-Resolution
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/resnetv2
Deep Koalarization: Image Colorization using CNNs and Inception-ResNet-v2
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_inception_v2
Deep Koalarization: Image Colorization using CNNs and Inception-ResNet-v2
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tsn
TSNAT: Two-Step Non-Autoregressvie Transformer Models for Speech Recognition
https://github.com/2023-MindSpore-1/ms-code-218/tree/main/opt
https://github.com/2023-MindSpore-1/ms-code-219/tree/main/duconv
Multiple Generative Models Ensemble for Knowledge-Driven Proactive Human-Computer Dialogue Agent
https://github.com/2023-MindSpore-1/ms-code-222/tree/main/CPNet
CPNet: Cross-Parallel Network for Efficient Anomaly Detection
https://github.com/2023-MindSpore-1/ms-code-222/tree/main/SGAE
https://github.com/2023-MindSpore-1/ms-code-224/tree/main/AdaBin
https://github.com/2023-MindSpore-1/ms-code-224/tree/main/Alexnet
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-5/tree/main/gnmt_v2
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
https://github.com/2023-MindSpore-1/ms-code-6/tree/main/cct
https://github.com/2023-MindSpore-1/ms-code-61
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://github.com/2023-MindSpore-1/ms-code-62
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://github.com/2023-MindSpore-1/ms-code-69
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/StyTr-2
https://github.com/2023-MindSpore-4/Code-5/tree/main/IndexNet
https://github.com/2023-MindSpore-4/Code-5/tree/main/m2det
M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network
https://github.com/2023-MindSpore-4/Code-5/tree/main/meta-baseline
https://github.com/2023-MindSpore-4/Code-5/tree/main/mobilenetV3_small_x1_0
https://github.com/2023-MindSpore-4/Code-5/tree/main/mobilenetv3_large
https://github.com/2023-MindSpore-4/Code10/tree/main/hardnet
https://github.com/2023-MindSpore-4/Code11/tree/main/STGAN
STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing
https://github.com/2023-MindSpore-4/Code11/tree/main/Segformer
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
https://github.com/2023-MindSpore-4/Code11/tree/main/SemanticHumanMatting
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/bloom
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.