The aligned feature space can help us build robust 3D representation even if bad proposals are given. Therefore, we devise a new contrast learning framework for indoor 3D object detection, called EFECL, that learns robust 3D representations by contrastive learning of proposals on two different levels.
Aug 3, 2023
The aligned feature space can help us build robust 3D representation even if bad proposals are given. Therefore, we devise a new contrast learning framework for ...
Contrastive learning provides a feasible way for representing proposals, which can align complete and incomplete/noisy proposals in feature space. The aligned ...
Contrastive learning provides a feasible way for representing proposals, which can align complete and incomplete/noisy proposals in feature space. The aligned ...
[PDF] ARM3D: Attention-based relation module for indoor 3D object ...
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EFECL: Feature encoding enhancement with contrastive learning for indoor 3D object detection · Multi-task learning and joint refinement between camera ...
EFECL: Feature encoding enhancement with contrastive learning for indoor 3D object detection ... 3D rigid object based on edge-enhanced point pair features.
Keyword: contrastive learning. Research Article | Open Access. EFECL: Feature encoding enhancement with contrastive learning for indoor 3D object detection.
Open Access 03.08.2023 | Research Article. EFECL: Feature encoding enhancement with contrastive learning for indoor 3D object detection.
EFECL: Feature encoding enhancement with contrastive learning for indoor 3D object detection. 2023, Computational Visual Media. Peelmesh: Precisely Peel Off ...
May 27, 2024 · We propose a novel ContrastAlign approach that utilizes contrastive learning to enhance the alignment of heterogeneous modalities, thereby improving the ...
Missing: EFECL: encoding indoor