https://github.com/liyi01827/noisy-contrastive
Bootstrap your own latent: A new approach to self-supervised Learning
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/ljy-hy/mentormix_pytorch
https://github.com/lkeonwoo94/DL_cv-mdt_NVIDIA_Cert_Course_StudyPI
https://github.com/llzlcl/pointcloud-segment
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/lpirola13/flower-recognizer
https://github.com/lpirola13/flower_recognizer
https://github.com/ls-da3m0ns/DeepSort_with_yolov5
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/ls-da3m0ns/Multiple-Object-Tracking
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/ls-da3m0ns/Short-ResNet
https://github.com/lsh110600/person_re_id
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/lucidrains/byol-pytorch
Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/lulujianjie/person-reid-tiny-baseline
Bag of Tricks and A Strong Baseline for Deep Person Re-identification
https://github.com/lxy000719/ResNet-50-pneumonia-classification
https://github.com/lyakaap/NetVLAD-pytorch
https://github.com/lywang12/cupi-domain
https://github.com/lywang12/cuti-domain
https://github.com/lyy973/OSFA
Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro
https://github.com/lzx551402/ASLFeat
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/lzx6/pytorch_DA
https://github.com/mabhay3420/Deep-Into-CNN
https://github.com/maciejdomagala/DLWP_notes
https://github.com/magnificent1208/r3det-on-mmdetection
https://github.com/mahmoodlab/hest
https://github.com/makatx/YOLO_ResNet
https://github.com/malin9402/2020-0221
https://github.com/mandiehyewon/goodviews_ecg
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/manoranjan03/PaperImplementations
https://github.com/maosnhehe/RIPR
https://github.com/mariaauslander/capstone_fall20_irrigation
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/marlcplhra/ShuffleNet
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/marload/ConvNets-TensorFlow2
https://github.com/mashaan14/DANN-toy
https://github.com/masoudnick/brain-tumor-mri-classification
https://github.com/matakshay/Neural_Image_Caption_Generator
https://github.com/mathildor/DeepLab-v3
https://github.com/maxwelltsai/DeepGalaxy
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.