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/code-implementation1/Code7/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/code-implementation1/Code7/tree/main/resnetv2
https://github.com/code-implementation1/Code9/tree/main/vgg
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/coderwangson/Face-anti-spoofing-based-on-color-texture-analysis
https://github.com/coderwangson/Learn-Convolutional-Neural-Network-for-Face-Anti-Spoofing_pytorch
https://github.com/cornell-zhang/allo-pldi24-artifact
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/cryu854/ArbitraryStyle
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/cryu854/ArbitraryStyle-tfjs
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/daimonae/Fundus-Image-Classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/danielamassiceti/CCA-visualdialogue
https://github.com/danielparada1/RL_SpaceInvaders
https://github.com/darrishabh/coviprox
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/datawiz1984/MLND_Capstone_Project
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/datawiz1984/malaria-model
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/datoboat/Vehicle-Detection
https://github.com/dead-mazai/avia-missing-airplanes
https://github.com/decayale/vlocnet
Deep Auxiliary Learning for Visual Localization and Odometry
https://github.com/deepmind/dm-haiku
https://github.com/deepmodeling/deepmd-kit
https://github.com/deepquestai/fire-smoke-dataset
https://github.com/demul/ResidualNet
https://github.com/deontaepharr/Residual-Attention-Network
https://github.com/dishen12/py03
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/djwhsdj/vw-sdk
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/dmizr/phuber
https://github.com/dnddnjs/pytorch-cifar10
https://github.com/doantienthongbku/Implementation-patchnet
PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognition
https://github.com/dssbxx/k_labels_resnet50
https://github.com/duchaba/Norwegian_Blue_Parrot_k2fa_AI
https://github.com/ebnerluca/uw_depth
FLSea: Underwater Visual-Inertial and Stereo-Vision Forward-Looking Datasets
https://github.com/ehijano/Faster-RCNN-Global-Wheat-Detection
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/elliott-iadvize/ocr-aws-distributed
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/enzomuschik/distilfnd
https://github.com/eric-erki/IdenProf
https://github.com/event-driven-robotics/bimvee
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.