https://github.com/tiancity-NJU/da-faster-rcnn-PyTorch
Domain Adaptive Faster R-CNN for Object Detection in the Wild
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Domain Adaptation is the task of adapting models across domains. This is motivated by the challenge where the test and training datasets fall from different data distributions due to some factor. Domain adaptation aims to build machine learning models that can be generalized into a target domain and dealing with the discrepancy across domain distributions.
Further readings:
<span style="color:grey; opacity: 0.6">( Image credit: Unsupervised Image-to-Image Translation Networks )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Domain Adaptive Faster R-CNN for Object Detection in the Wild
Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions
Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Mind the Domain Gap: a Systematic Analysis on Bioacoustic Sound Event Detection
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Learning Generalisable Omni-Scale Representations for Person Re-Identification
Towards Robust Robot 3D Perception in Urban Environments: The UT Campus Object Dataset
Robust and Generalizable Visual Representation Learning via Random Convolutions
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Very Deep Convolutional Networks for Large-Scale Image Recognition
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Bag of Tricks for Image Classification with Convolutional Neural Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.