Papers with Code 아카이브
Object
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 0
- 보존된 평가 기록
- 0
Replace the cat with a British Shorthair cat of the breed with bulging yellow eyes
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/collectionslab/annotations-computervision
https://github.com/collectionslab/book-annotation-classification
https://github.com/coolbay/VSGN
https://github.com/coperception/double-m-quantification
Uncertainty Quantification of Collaborative Detection for Self-Driving
https://github.com/craston/object_detection_cib
https://github.com/crowdai/crowdai-mapping-challenge-mask-rcnn
https://github.com/crowdflowTUe/stampnet
https://github.com/cruiseresearchgroup/DroTrack
DroTrack: High-speed Drone-based Object Tracking Under Uncertainty
https://github.com/cshizhe/maskrcnn_benchmark
https://github.com/csm-kr/Retinanet_pytorch
https://github.com/csmiler/tf-faster-rcnn-cpu
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/ctrlovefly/df4lcz
SAM-Assisted Remote Sensing Imagery Semantic Segmentation with Object and Boundary Constraints
https://github.com/cuihu1998/EfficientDet-d0
https://github.com/cuiziteng/illumination-adaptive-transformer
Getting to Know Low-light Images with The Exclusively Dark Dataset
https://github.com/cure-lab/magicdrive
MagicDrive: Street View Generation with Diverse 3D Geometry Control
https://github.com/cuzyoung/crossearth
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
https://github.com/cv516Buaa/tph-yolov5
https://github.com/cvfx-2019/homework3-GAN-Dissection
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
https://github.com/cvl-umass/ContrastLandmark
On Equivariant and Invariant Learning of Object Landmark Representations
https://github.com/cvlab-epfl/wide-depth-range-pose
https://github.com/cvlab-kaist/MUG-VOS
https://github.com/cvlab-yonsei/BANA
Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation
https://github.com/cwbabel/faster-cnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/cxiang26/stacked_capsule_autoencode_pl
https://github.com/cxmomo/Neighbor-Vote
Neighbor-Vote: Improving Monocular 3D Object Detection through Neighbor Distance Voting
https://github.com/cxt98/Densefusion-transparency
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
https://github.com/cy0616/data_augment
https://github.com/cyctrung/DPnet
https://github.com/d-ailin/blind-faith-in-text
https://github.com/d-robotics-ai-lab/dosod
https://github.com/d4vidbiertmpl/Solving-Visual-Object-Ambiguities-when-Pointing
Solving Visual Object Ambiguities when Pointing: An Unsupervised Learning Approach
https://github.com/dC4rlos/TFM
https://github.com/daerduoCarey/o2oafford
O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learning
https://github.com/dafanghe/Tensorflow_SceneText_Oriented_Box_Predictor
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/daijifeng001/MNC
Convolutional Feature Masking for Joint Object and Stuff Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.