https://github.com/marisancans/frame-predict
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
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/marload/ConvNets-TensorFlow2
https://github.com/martinruenz/maskfusion
MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects
https://github.com/mathiasroesler/machine_teaching
https://github.com/mattfeng/recurrent-extreme-occlusion
Robustness of Object Recognition under Extreme Occlusion in Humans and Computational Models
https://github.com/matthias-k/DeepGaze
Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet
https://github.com/mauriceweiler/MobiusCNNs
Why do deep convolutional networks generalize so poorly to small image transformations?
https://github.com/max-andr/joint-cnn-mrf
Learning Human Pose Estimation Features with Convolutional Networks
https://github.com/mayank-17/Project-Object-Recognition
https://github.com/mbuet2ner/local-global-features-cnn
https://github.com/mdda/deep-learning-models
https://github.com/mdenil/dropout
Improving neural networks by preventing co-adaptation of feature detectors
https://github.com/mdiephuis/simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/mdsarfarazulh/deep-texture-synthesis-cnn-keras
https://github.com/meet-minimalist/Texture-Synthesis-Using-Convolutional-Neural-Networks
https://github.com/menon92/WaveletCNN
https://github.com/mertyg/post-hoc-cbm
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/michi-3000/eyeclip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/microsoft/MLOps_VideoAnomalyDetection
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
https://github.com/microsoft/fb.resnet.torch
Some Improvements on Deep Convolutional Neural Network Based Image Classification
https://github.com/microsoft/unilm/tree/master/layoutlm
https://github.com/midusi/cacic2019-handshapes
https://github.com/mimikaan/Attention-Model
https://github.com/mindspore-ai/models/blob/master/research/cv/SPPNet
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
https://github.com/mindspore-ai/models/tree/master/official/cv/densenet
https://github.com/mindspore-ai/models/tree/master/official/cv/googlenet
https://github.com/mindspore-ai/models/tree/master/official/cv/simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/mindspore-courses/MindSpore-classification
https://github.com/mindspore-ecosystem/mindcv/blob/main/mindcv/models/densenet.py
https://github.com/mindspore-ecosystem/mindcv/blob/main/mindcv/models/googlenet.py
https://github.com/minggli/DenseNet
https://github.com/minhanh151/pre
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/minhanh151/respro
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/minimaxir/person-blocker
https://github.com/miraclewkf/densenet
https://github.com/ml-jku/cloob
Learning Transferable Visual Models From Natural Language Supervision
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.