https://github.com/kawshik8/DL-project
A Simple Framework for Contrastive Learning of Visual Representations
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/kbraunlich/contort_DNN
Adapting Deep Network Features to Capture Psychological Representations
https://github.com/kclip/neurodata
https://github.com/kclip/snn
https://github.com/keillernogueira/exploit-cnn-rs
https://github.com/kenkai21/Image_Captioning
https://github.com/kevinlisun/romans_stack
https://github.com/kingcong/densenet
https://github.com/kingcong/googlenet
https://github.com/kkhosla96/cs231n-project
https://github.com/klemens-floege/oneprot
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/km1414/CNN-models
https://github.com/kn-lambda/Pred-Net
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
https://github.com/krafton-ai/mini-batch-cl
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/krantirk/Face-detection-and-counting-
https://github.com/krish-thorcode/Object-Detection
https://github.com/krish-thorcode/Object-Recognition
https://github.com/krishnakarthi/COVID-19_Prediction
https://github.com/kunal-visoulia/Object-Recognition-Using-CNN
https://github.com/kunimasa-kawasaki/chainer-prednet
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
https://github.com/kunimasa-kawasaki/keras-prednet
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
https://github.com/kynkaat/role-of-imagenet-classes-in-fid
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/kyungsu-lee-ksl/ash
https://github.com/lab-midas/med_segmentation
https://github.com/leaderj1001/Billion-scale-semi-supervised-learning
Billion-scale semi-supervised learning for image classification
https://github.com/leftthomas/SimCLR
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/lengstrom/gitlinks
https://github.com/leolee99/CLIP_ITM
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/leoliao2008/TensorflowMobileOfficialExample
https://github.com/liangheming/sparse_rcnnv1
Sparse R-CNN: End-to-End Object Detection with Learnable Proposals
https://github.com/lifelong-robotic-vision/lifelong-object-recognition-challenge
CORe50: a New Dataset and Benchmark for Continuous Object Recognition
https://github.com/lifesailor/data-driven-predictive-maintenance
Deep Learning and Its Applications to Machine Health Monitoring: A Survey
https://github.com/lifunudt/blender_based_render
https://github.com/lightly-ai/lightly
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/lim0606/caffe-googlenet-bn
https://github.com/linjieli222/hero_video_feature_extractor
Learning Transferable Visual Models From Natural Language Supervision
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.