Papers with Code 아카이브
Object Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 3
- 평가표
- 9
- 보존된 평가 기록
- 31
Object recognition is a computer vision technique for detecting + classifying objects in images or videos. Since this is a combined task of object detection plus image classification, the state-of-the-art tables are recorded for each component task here and here.
<span style="color:grey; opacity: 0.6">( Image credit: Tensorflow Object Detection API )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/lionelmessi6410/ntga
https://github.com/liuch37/image-processing
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/liunian-harold-li/desco
DesCo: Learning Object Recognition with Rich Language Descriptions
https://github.com/liuzhuang13/DenseNetCaffe
https://github.com/lixixibj/forecasting-with-time-series-imaging
https://github.com/lixixibj/tsImage-forecasting
https://github.com/lorebianchi98/fg-ovd
Is CLIP the main roadblock for fine-grained open-world perception?
https://github.com/lornatang/googlenet-pytorch
https://github.com/lpirola13/flower-recognizer
https://github.com/lpirola13/flower_recognizer
https://github.com/lrzpellegrini/CL-CORe-App
Rehearsal-Free Continual Learning over Small Non-I.I.D. Batches
https://github.com/lrzpellegrini/Fine-Grained-Continual-Learning
Rehearsal-Free Continual Learning over Small Non-I.I.D. Batches
https://github.com/lucaerculiani/towards-visual-semantics
https://github.com/lucasleesw/PCANet_python_ver
PCANet: A Simple Deep Learning Baseline for Image Classification?
https://github.com/lucidrains/DALLE2-pytorch
https://github.com/lucidrains/En-transformer
https://github.com/lucidrains/flash-cosine-sim-attention
https://github.com/lucidrains/linear-attention-transformer
https://github.com/lucidrains/memory-transformer-xl
https://github.com/lucidrains/stylegan2-pytorch
https://github.com/luckytiger123/dropmessage
Improving neural networks by preventing co-adaptation of feature detectors
https://github.com/lufan31/comprecap
https://github.com/luizgh/sigver
Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification
https://github.com/lunaproject22/rpa
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/mabhay3420/Deep-Into-CNN
https://github.com/maciejczyzewski/kck2019
Chessboard and chess piece recognition with the support of neural networks
https://github.com/maddin79/darch
Improving neural networks by preventing co-adaptation of feature detectors
https://github.com/madrylab/pretraining-distribution-shift-robustness
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/mainaksingha01/applenet
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/mainaksingha01/odg-clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/mandiehyewon/goodviews_ecg
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/manhcuongk55/gender-classification-by-hand
https://github.com/manthanpatel2/Object-Detection-on-a-Frame
https://github.com/mapleleaf6/zode
https://github.com/mariaauslander/capstone_fall20_irrigation
A Simple Framework for Contrastive Learning of Visual Representations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.