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/2023-MindSpore-4/Code7/tree/main/ssd_resnet_34
https://github.com/2023-MindSpore-4/Code9/tree/main/ResNet
https://github.com/2023-MindSpore-4/Code9/tree/main/VGG
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2024-MindSpore-1/Code7/tree/main/centernet_resnet101
https://github.com/2024-MindSpore-1/Code7/tree/main/centernet_resnet50_v1
https://github.com/3P2S/arcface
https://github.com/AIOSYM/dl-model-gallery
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/AbdallahMGomaa/PatchNet
PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognition
https://github.com/AdamHtooLwin/vigilant
https://github.com/Afsaan/CNN-Architectures
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Anderies/stochastic-constant-pruninglayers
https://github.com/AngusG/bn-advex-zhang-fixup
https://github.com/Aniket7/VGGNet-CNN-architecture
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Anuranjan-Kumar/kaggle_cats-vs-dogs
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ArifRaihan/Deeper-CNN-Architectures-for-Image-Classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/AveryGriffin/NarutoCV
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/AyushAniket/ResNET-and-various-normalizations
https://github.com/BIG-CHENG/FaceRec
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Baichenjia/Resnet
https://github.com/Bao-Jiarong/ResNet
https://github.com/BeanGreen247/Python-AI-Arts
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Burf/ResNet-Tensorflow2
https://github.com/CVxTz/face_age_gender
https://github.com/CanshangD/ResNet_tensorflow2.0
https://github.com/CellSMB/EM-net
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ChangweiZhang/Awesome-WindowsML-ONNX-Models
https://github.com/ChiWeiHsiao/DeepVO-pytorch
DeepVO: Towards End-to-End Visual Odometry with Deep Recurrent Convolutional Neural Networks
https://github.com/CocoSungMin/Gachon_SW_Colorization_Contest
https://github.com/CodeChefVIT/VOID
https://github.com/CorneliusHsiao/FoodMethodGAN
https://github.com/CrossEntropy/Gesture-images-recognition-ResidualNetwork
https://github.com/CryptoSalamander/pytorch_paper_implementation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/D-X-Y/ResNeXt-DenseNet
https://github.com/DMarwan/NutricIA
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/DableUTeeF/keras-efficientnet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.