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Pupil Tracking

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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평가표

1

보존된 평가 기록

2

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/javiribera/locating-objects-without-bboxes

공식 코드

Locating Objects Without Bounding Boxes

https://github.com/pbonazzi/retina

공식 코드

Retina : Low-Power Eye Tracking with Event Camera and Spiking Hardware

https://github.com/qinche106/cb-convlstm-eyetracking

공식 코드

3ET: Efficient Event-based Eye Tracking using a Change-Based ConvLSTM Network

https://github.com/timothygebhard/hsr4hci

공식 코드

Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal framework

https://github.com/HaipengXiong/weighted-hausdorff-loss

Locating Objects Without Bounding Boxes

https://github.com/N0vel/weighted-hausdorff-distance-tensorflow-keras-loss

Locating Objects Without Bounding Boxes

https://github.com/Nacriema/Loss-Functions-For-Semantic-Segmentation

Locating Objects Without Bounding Boxes

https://github.com/cedriclmenard/irislandmarks.pytorch

Real-time Pupil Tracking from Monocular Video for Digital Puppetry

https://github.com/danielenricocahall/Keras-Weighted-Hausdorff-Distance-Loss

Locating Objects Without Bounding Boxes

https://github.com/vnbot2/object-locator

Locating Objects Without Bounding Boxes

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.