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/yakhyo/head-pose-estimation
https://github.com/yakhyo/retinaface-pytorch
https://github.com/yangboz/TransferLearning4Dentist
https://github.com/yangorwell/NGPlus
https://github.com/yangyucheng000/densenet/blob/main/densenet.py
https://github.com/yangyucheng000/mobilenet_v2/blob/main/mobilenet_v2.py
https://github.com/yangyucheng000/resnet_Ascend
https://github.com/yangyucheng000/shufflenetv1/blob/main/shufflenetv1.py
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/yanx27/Pointnet_Pointnet2_pytorch
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/yaox12/BYOL-PyTorch
Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/yashclone999/ResNet_MODEL
https://github.com/ycao5602/SAL
https://github.com/ycxioooong/MovieSynopsisAssociation
Person Search in Videos with One Portrait Through Visual and Temporal Links
https://github.com/yibeiou/Advanced_Business_Intelligence
https://github.com/yichigo/Chest-X-Ray
https://github.com/yoojungsun0/Psych239
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/yoshitomo-matsubara/torchdistill
https://github.com/youngbin-ro/Homography-based-MOTDT
https://github.com/youngbin-ro/MOTDT-original
https://github.com/youwenjing/reid_mgn-dgnet
Learning Discriminative Features with Multiple Granularities for Person Re-Identification
https://github.com/yudhisteer/Face-Recognition-with-Masks
https://github.com/yujiacheng333/CircleLossMNIST
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/yujiang0922/Re-ID-Tracking
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/yumaloop/mobilenetV2-cifar
https://github.com/yusufsugiono/klasifikasi-gambar-bunga
https://github.com/yw0nam/DenseNet
https://github.com/zaiweizhang/H3DNet
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/zenroad/modifypointnet
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/zer0sh0t/artificial_intelligence/tree/master/self_supervised_learning_methods/bootstrap_your_own_latent
Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/zhangxinyu-xyz/PAST-ReID
Self-training with progressive augmentation for unsupervised cross-domain person re-identification
https://github.com/zhen8838/Circle-Loss
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/zhengziqiang/ReshapeGAN
https://github.com/zhh6425/LocalContextPropagation
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/zhh6425/MotionPointNet
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/zhunzhong07/person-re-ranking
Person Re-identification by Local Maximal Occurrence Representation and Metric Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.