https://github.com/Pealing/DDAN
Dual Distribution Alignment Network for Generalizable Person Re-Identification
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/Pecneb/computer_vision_research
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/Phoebe-star/AlignedReID
AlignedReID: Surpassing Human-Level Performance in Person Re-Identification
https://github.com/Phoebe-star/part_aligned
Deeply-Learned Part-Aligned Representations for Person Re-Identification
https://github.com/PolinaDruzhinina/mobilenet
https://github.com/PolinaDruzhinina/modelnet
https://github.com/Proxim123/person-reID-No1-
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/PuchatekwSzortach/combination_of_multiple_global_descriptors_for_image_retrieval
https://github.com/Punakshi/Deep-Residual-Learning-for-Image-Recognition-Implementation
https://github.com/QizaoWang/CAMC-CCReID
https://github.com/RRoundTable/OceanLitter_dataset_generator
https://github.com/RaghavHub/rekuten_hack
https://github.com/RajdeepBiswas/Manufacturing-Quality-Inspection
https://github.com/RajuGudhe/Cancer_Tissue_Detection
https://github.com/Rakshit-Shetty/Resnet-Implementation
https://github.com/RameshBattu/Convolutional-Neural-Network-on-CIFAR-10-DataSet
https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/Recognito-Vision/Face-SDK-Linux-Demos
https://github.com/Recognito-Vision/Linux-FaceRecognition-FaceLivenessDetection
https://github.com/RemyMess/MMVRC_ICCV_2021_Skeleton_based_Action_Recognition
UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicles
https://github.com/ReshinthAdith/BYOL-Pytorch
Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/Robinatp/Deeplab_Tensorflow
https://github.com/RobotMobile/cv-deep-learning-paper-review
https://github.com/Robotmurlock/Motrack
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/RodMech/OSNet-IBN1-Lite
https://github.com/Rohed/ml-1
https://github.com/RunzhaoHuang/DeepSort_YOLOV5_OnScreen
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/SANKHA1/Vehicle-Detection
https://github.com/SJTU-Thinklab-Det/r3det-on-mmdetection
https://github.com/SY-Xuan/pointnet_plus_plus_paddlepaddle
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/SaeedShurrab/SimSiam-pytorch
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/SaeedShurrab/Simple-BYOL
Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/Sakib1263/1DResNet-Builder-KERAS
https://github.com/Sakib1263/1DResNet-KERAS
https://github.com/Sakib1263/DenseNet-1D-2D-Tensorflow-Keras
https://github.com/Sakib1263/MobileNet-1D-2D-Tensorflow-Keras
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.