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/witignite/Frustum-PointNet
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/wondonghyeon/protest-detection-violence-estimation
https://github.com/wujpbb7/caffe_circleloss
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/wuqiyao20160118/mini_project-for-CIFAR10
https://github.com/wuyang1903220154/Video-based-person-ReID-with-Attribute-information
Attribute-aware Identity-hard Triplet Loss for Video-based Person Re-identification
https://github.com/wvangansbeke/Unsupervised-Classification
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/wxb589/Person_reID_baseline_pytorch-master
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/wxb589/softened-similarity-learning
Unsupervised Person Re-identification via Softened Similarity Learning
https://github.com/wy-moonind/trackrcnn_with_deepsort
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/xTRam1/Object-Detection-on-Custom-Dataset
https://github.com/xcmyz/Face-Binary-Classification
https://github.com/xcmyz/FaceDetection
https://github.com/xcmyz/Face_Binary_Classfication
https://github.com/xf1994/good_practices_for_person_reID
Towards Good Practices on Building Effective CNN Baseline Model for Person Re-identification
https://github.com/xhlulu/arxiv-assistant
https://github.com/xiaochus/MobileNetV2
https://github.com/xiaomingzhid/sskd
Semi-Supervised Domain Generalizable Person Re-Identification
https://github.com/xiaoxiong74/Object-Detection-and-Tracking
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/xiaoyufenfei/LEDNet
https://github.com/xinkuansong/modified-resnet-acc-0.9638-10.7M-parameters
https://github.com/xiuyu0000/papers_with_examples/blob/main/MobileNet/mobilenetv2.ipynb
https://github.com/xiuyu0000/papers_with_examples/tree/main/cancer_detection_demo
https://github.com/xiuyu0000/tutorials/tree/main/mobilenetv2
https://github.com/xiuyu0000/tutorials/tree/main/resnet
https://github.com/xiuyu0000/vision/blob/main/mindvision/classification/models/backbones/mobilenet_v2.py
https://github.com/xiuyu0000/vision/blob/main/mindvision/classification/models/resnet.py
https://github.com/xr-Yang/MGN-Pytorch
Learning Discriminative Features with Multiple Granularities for Person Re-Identification
https://github.com/xslidi/EfficientNets_ddl_apex
https://github.com/xufanxiong/classification-of-caltech-256
https://github.com/xurui1217/pointnet2-master
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/xuxu116/pytorch-reid-lite
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/xxradon/IGCV3-pytorch
https://github.com/xypan1232/iDeepE
https://github.com/yahoo/open_nsfw
https://github.com/yakhyo/EfficientNet-PyTorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.