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Supervised Only 3D Point Cloud Classification
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/chalothon/BERT_Practice
https://github.com/chandu7077/mybert
https://github.com/charlesq34/pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/charlesq34/pointnet2
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/chen-xiong-yi/OwnBERT
https://github.com/chengchingwen/transformers.jl
https://github.com/chiayewken/bert-qa
https://github.com/chrisleunglokhin/Capstone-BERT
https://github.com/christianspybrook/article_recommender
https://github.com/cloudmcloudyo/capstone
https://github.com/cmsflash/efficient-attention
https://github.com/coco60/bert-test
https://github.com/coconutzs/PointNet_zs
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/colorfulscoop/tfdlg
https://github.com/conceptofmind/LaMDA-pytorch
https://github.com/conceptofmind/lamda-rlhf-pytorch
https://github.com/coronazap/bert_client
https://github.com/cosmoquester/seq2seq
https://github.com/cospplay/bert-master
https://github.com/coxy1989/tfmr
https://github.com/cpm0722/transformer_pytorch
https://github.com/cuber2460/bert
https://github.com/curryyuan/x-trans2cap
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/cy-xu/spatially_aware_ai
https://github.com/cyberzhg/keras-pos-embd
https://github.com/czero69/acomoeye-NN
https://github.com/davidalbertonogueira/NLP-tutorials
https://github.com/davisking/dlib-models
https://github.com/dccuchile/CC6204
https://github.com/debajyotid2/pointnet_pl
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/deepmind/haiku
https://github.com/deepmipt/bert/tree/feat/multi_gpu
https://github.com/demelin/nematode
https://github.com/derylucio/Transformer
https://github.com/dfki-av/mikasa-3dvg
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.