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Video Object Detection
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Video object detection is the task of detecting objects from a video as opposed to images.
<span style="color:grey; opacity: 0.6">( Image credit: Learning Motion Priors for Efficient Video Object Detection )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/towhee-io/towhee/tree/main/towhee/models/tsm
TSM: Temporal Shift Module for Efficient Video Understanding
https://github.com/ttt496/vit-pytorch
https://github.com/valeoai/LOST
https://github.com/valeoai/found
https://github.com/vikrant7/mobile-vod-bottleneck-lstm
Mobile Video Object Detection with Temporally-Aware Feature Maps
https://github.com/vikrant7/pytorch-looking-fast-and-slow
Looking Fast and Slow: Memory-Guided Mobile Video Object Detection
https://github.com/vturrisi/solo-learn
https://github.com/waltersimoncini/fungivision
https://github.com/woctezuma/steam-DINO
https://github.com/yimingcuicuicui/faq
FAQ: Feature Aggregated Queries for Transformer-based Video Object Detectors
https://github.com/youthHan/HVRNet
https://github.com/yueatsprograms/ttt_imagenet_release
https://github.com/zer0sh0t/artificial_intelligence/tree/master/self_supervised_learning_methods/self_distillation_with_no_labels
https://gitlab.com/birder/birder
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.