태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
The objective of this challenge is to automate the process of estimating the soil parameters, specifically, potassium (KKK), phosphorus pentoxide (P2O5P_2O_5P2O5), magnesium (MgMgMg) and pHpHpH, through extracting them from the airborne hyperspectral images captured over agricultural areas in Poland (the exact locations are not revealed). To make the solution applicable in real-life use cases, all the parameters should be estimated as precisely as possible.
관련 논문에서 소개한 기법입니다. 이 태스크에서의 평가 여부는 평가 결과에서 확인하세요.
A FuseFormer block is used in the FuseFormer model for video inpainting. It is the same to standard Transformer block except that feed forward network is replaced with a Fusion Feed Forward Network (F3N). F3N brings no extra parameter into the standard feed forward net and the difference is that F3N inserts a soft-split and a soft composite operation between the two layer of MLPs.
FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting
Soft Split and Soft Composition are video frame based operations used in the FuseFormer architecture, specifically the FuseFormer blocks. We softly split each frame into overlapped patches and then softly composite them back, by using an unfold and fold operator with patch size $k$ being greater than patch stride $s$. When compositing patches back to its original spatial shape, we add up feature values at each overlapping spatial location of neighboring patches.
FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.