Papers with Code 아카이브
Person Re-Identification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 13
- 평가표
- 41
- 보존된 평가 기록
- 533
Person Re-Identification is a computer vision task in which the goal is to match a person's identity across different cameras or locations in a video or image sequence. It involves detecting and tracking a person and then using features such as appearance, body shape, and clothing to match their identity in different frames. The goal is to associate the same person across multiple non-overlapping camera views in a robust and efficient manner.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ariangc/breinchallenge
https://github.com/arnavdodiedo/DenseNet-Fashion-MNIST
https://github.com/arnavdodiedo/DenseNet-MNIST
https://github.com/aryanasadianuoit/MobileNet_V2
https://github.com/asad-62/IVP-DNN
https://github.com/asahi417/DeepDomainAdaptation
https://github.com/asalarpour/Point_GN
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/asd08573064/SimCLR
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/ashishpatel26/BrainMRI-Segmentation-Keras
https://github.com/aslialp/HATCNN
Torchreid: A Library for Deep Learning Person Re-Identification in Pytorch
https://github.com/asmerdov/DataCollectionSystem
https://github.com/asprenger/keras_fc_densenet
https://github.com/astoycos/Mini_Project2
https://github.com/atapour/ransomware-classification
https://github.com/aurelien-peden/Deep-Learning-paper-implementations
https://github.com/avocardio/resnet_vs_convnext
https://github.com/axmoyal/Steganalysis-with-CNN
https://github.com/ayoolaolafenwa/orangelib
https://github.com/ayushpatidar/PR1-DenseNet
https://github.com/azima-fariha/DeepLearning_DenselyConnectedConvolutionalNetworks
https://github.com/b8goal/PIRL-Residual-network
https://github.com/bamos/densenet.pytorch
https://github.com/barmayo/spatial_attention
https://github.com/bastiennNB/Pair_ReID
https://github.com/bbednarski9/MaskTrackRCNN_DeepSort
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/bclwan/MRI_Brain_Segmentation
https://github.com/ben-davidson-6/fixup
https://github.com/bentrevett/pytorch-image-classification
https://github.com/beresandras/contrastive-classification-keras
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/bertrandlalo/deep_dog_breeds
https://github.com/bethgelab/InDomainGeneralizationBenchmark
https://github.com/bfortuner/pytorch_tiramisu
https://github.com/bhaskar-gaur/DenseNet-Keras
https://github.com/bhumigodiwala/Face-Mask-Detection
https://github.com/bjader/QSSL
A Simple Framework for Contrastive Learning of Visual Representations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.