Papers with Code 아카이브
Visual Odometry
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 1
- 보존된 평가 기록
- 1
Visual Odometry is an important area of information fusion in which the central aim is to estimate the pose of a robot using data collected by visual sensors.
Source: Bi-objective Optimization for Robust RGB-D Visual Odometry
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/lucylow/salty-wet-man
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/lxy000719/ResNet-50-pneumonia-classification
https://github.com/lyk19940625/MyRFBNet
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/m1234d/build18
ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras
https://github.com/mabhay3420/Deep-Into-CNN
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/maciejdomagala/DLWP_notes
https://github.com/mackitron/COVID19
Very Deep Convolutional Networks for Large-Scale Image Recognition
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/manankshastri/ART
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/manoranjan03/PaperImplementations
https://github.com/marload/ConvNets-TensorFlow2
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/masoudnick/brain-tumor-mri-classification
https://github.com/matakshay/Neural_Image_Caption_Generator
https://github.com/maxwelltsai/DeepGalaxy
https://github.com/mbsariyildiz/resnet-pytorch
https://github.com/mdda/deep-learning-models
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/megvii-research/basecls/tree/main/zoo/public/resnet
https://github.com/megvii-research/basecls/tree/main/zoo/public/vgg
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mgonzalezrivero/reef_learning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mhagiwara/nanigonet
https://github.com/microsoft/fb.resnet.torch
https://github.com/mikekestemont/deepscript
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindlab-ai/mindcv/blob/main/examples/train_cifar_dynamic.py
https://github.com/mindlab-ai/mindcv/blob/main/mindcv/models/resnet.py
https://github.com/mindlab-ai/mindcv/blob/main/mindcv/models/vgg.py
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet50_quant
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet_thor
https://github.com/mindspore-ai/models/tree/master/official/cv/vgg16
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindspore-ai/models/tree/master/research/cv/FaceAttribute
https://github.com/mindspore-ai/models/tree/master/research/cv/vgg19
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/backbone/resnet.py
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.