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/pwc-1/Paper-9/tree/main/6/MVD
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification
https://github.com/pyaf/DenseNet-MURA-PyTorch
https://github.com/pytorch/vision
https://github.com/pytorch/vision/blob/main/torchvision/models/densenet.py
https://github.com/qianjinhao/circle-loss
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/qubvel/efficientnet
https://github.com/qubvel/resnet_152
https://github.com/qychen13/ClusterAlignReID
Cluster-level Feature Alignment for Person Re-identification
https://github.com/r-or/deep_sort
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/radiradev/contrastive-neutrino
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/rafaelmata357/Flower-image-classifier
https://github.com/raghakot/keras-resnet
https://github.com/rahimentezari/datadistributiontransferlearning
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/rahul-t-p/ASVspoof-2019
https://github.com/rahulchaurasiya1/cautious-waddle
https://github.com/raisinglc/object_detection_SSD
https://github.com/rajatkoner08/oodformer
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/rajkumargithub/densenet.mura
https://github.com/rajneeshaggarwal/google-efficientnet
https://github.com/rdbch/simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/rdbch/tutorial_simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/realmichaelye/Skin-Lesions-Classifier-ResNet50
https://github.com/rechardchen123/Crowded_analysis
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/reeered/ISR
Identity-Seeking Self-Supervised Representation Learning for Generalizable Person Re-identification
https://github.com/referit3d/referit3d
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/reppy4620/SimCLR4Paint
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/researchmm/SiamDW
https://github.com/reshinthadithyan/BYOL-Pytorch
Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/richmondvan/melanoma-detection
https://github.com/rickyHong/Random-erasing-Data-Augumentation-repl
https://github.com/rickyHong/tfRecord-Caltech256-repl2
https://github.com/rishabmallick/Sign-language-live-predictor
https://github.com/rlagywns0213/cifar100_data_augmentation
https://github.com/rmastand/jetclr_ad
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/robertofranceschi/Image-classification-on-Caltech101-using-CNNs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.