Papers with Code 아카이브
LIDAR Semantic Segmentation
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/okkteam/Transformer-Transducer
https://github.com/ololo123321/maestro
https://github.com/open-mmlab/mmclassification
https://github.com/open-mmlab/mmdetection
https://github.com/open-mmlab/mmdetection3d
CENet: Toward Concise and Efficient LiDAR Semantic Segmentation for Autonomous Driving
https://github.com/opencv/openvino_training_extensions
https://github.com/opennmt/ctranslate2
https://github.com/openvinotoolkit/training_extensions
https://github.com/owainwest/uniprot_bert
https://github.com/paolanu/BERT_epitope
https://github.com/parcorelab/comscribe
https://github.com/patrickhart/jaxdl
https://github.com/paulskeie/stadnamn
https://github.com/paulwarkentin/tf-ssd-vgg
https://github.com/pengming617/bert_classification
https://github.com/pengshuyuan/Bert
https://github.com/penny9287/sockeye
https://github.com/pennylaneai/generative-quantum-states
https://github.com/pesong/ssd-caffe
https://github.com/pessimiss/ai100-w8-master
https://github.com/phohenecker/pytorch-transformer
https://github.com/pierluigiferrari/ssd_keras
https://github.com/pingheng001/Cnn-Bert
https://github.com/piquil/rydberggpt
https://github.com/pjlab-adg/openpcseg
Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
https://github.com/plkmo/Transformer-Eng2French
https://github.com/plusmultiply/mprm
KPConv: Flexible and Deformable Convolution for Point Clouds
https://github.com/poel22/covproject
https://github.com/pomonam/AttentionCluster
https://github.com/prabhupad26/100daysofML
https://github.com/pritam1322/Machine-Translation-with-Transformer
https://github.com/pwc-1/Paper-9/tree/main/4/Translation-Invariant/model
https://github.com/pytorch/vision
https://github.com/qfgaohao/pytorch-ssd
https://github.com/radoslawkrolikowski/sentiment-analysis-pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.