Papers with Code 아카이브
Long-tail Learning
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Long-tailed learning, one of the most challenging problems in visual recognition, aims to train well-performing models from a large number of images that follow a long-tailed class distribution.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/j3soon/arxiv-utils
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
https://github.com/jackhck/subclass-balancing-contrastive-learning
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
https://github.com/jfc4050/detect-to-track
https://github.com/jhaprince/multibully
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/jiajunhua/facebookresearch-Detectron
https://github.com/jianhongbai/bacon
On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning
https://github.com/jndeng/DACSDC-DeepZ
https://github.com/joheras/darknet-colab
https://github.com/jolibrain/caffe
https://github.com/juergenlandauer/Maya-Challenge
https://github.com/kalelpark/ral
https://github.com/karan96/NewOne
https://github.com/karurb92/ldam_str_bn
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
https://github.com/kawshik8/DL-project
https://github.com/keke921/h2t
https://github.com/khaled2ahmed/k2a
https://github.com/klemens-floege/oneprot
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/kongzhiyou/darknet-master
https://github.com/kornia/kornia
https://github.com/kuangliu/pytorch-fpn
https://github.com/kvijaykrish/Bosch_AI_VehicleClassification
https://github.com/kynkaat/role-of-imagenet-classes-in-fid
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/kyunghwan/darknet_v3
https://github.com/leolee99/CLIP_ITM
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/lhcezx/Graph-FPN
https://github.com/li-yibing/oceannet
https://github.com/lijian16/fcc
https://github.com/linjieli222/hero_video_feature_extractor
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/liyemei/Deformable-active-convolutional
https://github.com/llsouder/screen-ocr
https://github.com/lunaproject22/rpa
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/lyk19940625/MyRFBNet
https://github.com/madrylab/pretraining-distribution-shift-robustness
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/magnificent1208/r3det-on-mmdetection
https://github.com/mainaksingha01/applenet
Learning Transferable Visual Models From Natural Language Supervision
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.