119 citations · 156 across the 24 of their papers we have counts for
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cs.CV2022★ 1 cited
PØDA: Prompt-driven Zero-shot Domain Adaptation
Mohammad Fahes, Tuan-Hung Vu, Andrei Bursuc +2
Domain adaptation has been vastly investigated in computer vision but still requires access to target images at train time, which might be intractable in some uncommon conditions.…
cs.CV2022
SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields
Anh-Quan Cao, Raoul de Charette
3D reconstruction from a single 2D image was extensively covered in the literature but relies on depth supervision at training time, which limits its applicability. To relax the de…
cs.CV2022★ 2 cited
COARSE3D: Class-Prototypes for Contrastive Learning in Weakly-Supervised 3D Point Cloud Segmentation
Rong Li, Anh-Quan Cao, Raoul de Charette
Annotation of large-scale 3D data is notoriously cumbersome and costly. As an alternative, weakly-supervised learning alleviates such a need by reducing the annotation by several o…