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/UnofficialJuliaMirrorSnapshots/DeepMark-deepmark
https://github.com/Vamshi399/CarND-Vehicle-Detection
https://github.com/VamsiKrishna1211/gender_age-detection
https://github.com/VhalPurohit/290s
https://github.com/Vignesh-95/cnn-semantic-segmentation-satellite-images
https://github.com/Vill-Lab/2021-TIP-IGOAS
https://github.com/Vill-Lab/2022-TIP-HCGA
https://github.com/VinayBN8997/CIFAR-10-object-detection
https://github.com/VinayBN8997/ResNet-CIFAR10
https://github.com/VisualComputingInstitute/triplet-reid
https://github.com/ViswanathaReddyGajjala/EfficientNet-RetinaNet
https://github.com/WangTaoAs/MGN_ReID
Learning Discriminative Features with Multiple Granularities for Person Re-Identification
https://github.com/WangYQ9/VideoReID_PSTA
https://github.com/Westlake-AI/openmixup
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/Wordbe/MobileNetV2
https://github.com/WuPedin/Multi-class_Yolov5_DeepSort_Pytorch
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/WuRui-Ella/Myfirststore
Joint Discriminative and Generative Learning for Person Re-identification
https://github.com/XG293/SupConLoss
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/XavierCHEN34/ClickSEG
https://github.com/Xiangxu-0103/Octant-CNN
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/XingangPan/IBN-Net
A Strong Baseline and Batch Normalization Neck for Deep Person Re-identification
https://github.com/XuyangBai/D3Feat
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/Yanghojun/Custom_yolov5_pytorch
https://github.com/Yeeun-Lee/parrot_proj1
https://github.com/Yeeun-Lee/parrot_vision_competition
https://github.com/YerevaNN/DIIN-in-Keras
https://github.com/Yimin-Yuan/VeinProject
https://github.com/YixuanLi/densenet-tensorflow
https://github.com/YudeWang/UNet-Satellite-Image-Segmentation
https://github.com/ZQPei/deep_sort_pytorch
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/ZXdatascience/TextDetectorAndroid
https://github.com/Zachdr1/CNNs
https://github.com/ZhangwenguangHikvision/YoloV5_JDE_TensorRT_for_Track
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/ZhaoJ9014/Multi-Human-Parsing
https://github.com/a07458666/simsiamfacenet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.