https://github.com/stigma0617/maskrcnn-benchmark-vovnet
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
Papers with Code 아카이브
Small Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Small Object Detection is a computer vision task that involves detecting and localizing small objects in images or videos. This task is challenging due to the small size and low resolution of the objects, as well as other factors such as occlusion, background clutter, and variations in lighting conditions.
<span style="color:grey; opacity: 0.6">( Image credit: Feature-Fused SSD )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/suvasis/birdnet2cs231n
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
https://github.com/vladan-stojnic/Detection-of-Small-Flying-Objects-in-UAV-Videos
https://github.com/vov-net/VoVNet-Detectron
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
https://github.com/vov-net/VoVNet-FCOS
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
https://github.com/youngwanLEE/VoVNet-RefineDet
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
https://github.com/youngwanLEE/vovnet-detectron2
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
https://github.com/zzl-pointcloud/Data_Augmentation_Zoo_for_Object_Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.