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/mdda/deep-learning-models
https://github.com/mdiephuis/simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/mdv3101/DeepSort_Yolo
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/megvii-research/basecls/tree/main/zoo/public/mbnet
https://github.com/megvii-research/basecls/tree/main/zoo/public/resnet
https://github.com/meijieru/yet_another_mobilenet_series
https://github.com/mg2033/shufflenet
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/mhagiwara/nanigonet
https://github.com/michiel-j/DANN-two-moons-PyTorch
https://github.com/microsoft/fb.resnet.torch
https://github.com/midusi/cacic2019-handshapes
https://github.com/mikel-brostrom/Yolov3_DeepSort_Pytorch
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/mikel-brostrom/Yolov5_DeepSort_Pytorch
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/mikel-brostrom/boxmot
https://github.com/mikel-brostrom/yolov7_strongsort_osnet
https://github.com/milkplz/keras-frcnn
https://github.com/mindlab-ai/mindcv/blob/main/examples/train_cifar_dynamic.py
https://github.com/mindlab-ai/mindcv/blob/main/mindcv/models/resnet.py
https://github.com/mindlab-ai/mindcv/blob/main/mindcv/models/shufflenetv1.py
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/mindspore-ai/contrib/tree/master/application/Spatial%20and%20Temporal%20Mutual%20Promotion%20for%20Video-based%20Person%20Re-identification
Spatial and Temporal Mutual Promotion for Video-based Person Re-identification
https://github.com/mindspore-ai/models/blob/master/official/cv/shufflenetv1
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/mindspore-ai/models/blob/master/research/cv/metric_learn
Beyond triplet loss: a deep quadruplet network for person re-identification
https://github.com/mindspore-ai/models/tree/master/official/cv/Deepsort
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/mindspore-ai/models/tree/master/official/cv/densenet
https://github.com/mindspore-ai/models/tree/master/official/cv/mobilenetv2
https://github.com/mindspore-ai/models/tree/master/official/cv/mobilenetv2_quant
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet50_quant
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet_thor
https://github.com/mindspore-ai/models/tree/master/official/cv/simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/mindspore-ai/models/tree/master/research/cv/AlignedReID
AlignedReID: Surpassing Human-Level Performance in Person Re-Identification
https://github.com/mindspore-ai/models/tree/master/research/cv/DDAG
Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification
https://github.com/mindspore-ai/models/tree/master/research/cv/FaceAttribute
https://github.com/mindspore-ai/models/tree/master/research/cv/MVD
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification
https://github.com/mindspore-ai/models/tree/master/research/cv/PAMTRI
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.