https://github.com/Galaxfy/ReID-test1
Learning Granularity-Unified Representations for Text-to-Image Person Re-identification
Papers with Code 아카이브
Person Re-Identification
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- 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/GeekAlexis/Constrained-Object-Tracking
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/GeekAlexis/Guardian
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/GeekAlexis/fast_mot
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/GeoTrouvetout/Vehicle_ReID
https://github.com/Ghailen-Ben-Achour/PointNet2_Segmentation
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/Ghiara/diva
https://github.com/Gideon0805/Tensorflow1.15-Model-Pruning
https://github.com/Gideon0805/Tensorflow_Model_Pruning
https://github.com/Glp91/fire-detection
https://github.com/GordonnW/ShuffleNetV1
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/Graylab/deepH3-distances-orientations
https://github.com/GuHongyang/Person-ReID-Pytorch
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/HHTseng/video-classification
https://github.com/HLinShan/vision_networks
https://github.com/HRanWang/SA
Parameter-Free Spatial Attention Network for Person Re-Identification
https://github.com/HRanWang/Spatial-Attention
Parameter-Free Spatial Attention Network for Person Re-Identification
https://github.com/Halesu/4th-ML100Days
https://github.com/HaoJunNM/Unet-PretrainedMobilenetV2encoder-Flaskapp
https://github.com/Haoyu1004/AGW_mindspore
Deep Learning for Person Re-identification: A Survey and Outlook
https://github.com/HarmanDotpy/Normalizations-in-Deep-Learning
https://github.com/Harut0726/votenet
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/Hashir44/muraxray
https://github.com/HibikiJie/BYOL
Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/HoYoung1/image-embedding
A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets
https://github.com/HobbitLong/PyContrast
https://github.com/HobbitLong/SupContrast
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/HoganZhang/Person_reID_baseline_pytorch
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/Hossein-Bodaghi/SI_attributes
https://github.com/IBM/NeuronAlignment
https://github.com/IMvision12/keras-vision-models
https://github.com/IcewineChen/mxnet-batch_hard_triplet_loss
https://github.com/InnovArul/vidreid_cosegmentation
https://github.com/IyatomiLab/CE-CLCNN
https://github.com/JContro/pytorch_projects
https://github.com/JHLee0513/Salt_detection_challenge
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.