107 citations · 236 across the 32 of their papers we have counts for
6 papers · 1 filter
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.…
Active Learning Strategies for Weakly-supervised Object Detection
Huy V. Vo, Oriane Siméoni, Spyros Gidaris +3
Object detectors trained with weak annotations are affordable alternatives to fully-supervised counterparts. However, there is still a significant performance gap between them. We…
LaRa: Latents and Rays for Multi-Camera Bird's-Eye-View Semantic Segmentation
Florent Bartoccioni, Éloi Zablocki, Andrei Bursuc +3
Recent works in autonomous driving have widely adopted the bird's-eye-view (BEV) semantic map as an intermediate representation of the world. Online prediction of these BEV maps in…
Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data
Corentin Sautier, Gilles Puy, Spyros Gidaris +3
Segmenting or detecting objects in sparse Lidar point clouds are two important tasks in autonomous driving to allow a vehicle to act safely in its 3D environment. The best performi…
What to Hide from Your Students: Attention-Guided Masked Image Modeling
Ioannis Kakogeorgiou, Spyros Gidaris, Bill Psomas +4
Transformers and masked language modeling are quickly being adopted and explored in computer vision as vision transformers and masked image modeling (MIM). In this work, we argue t…
Drive&Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-modal Distillation
Antonin Vobecky, David Hurych, Oriane Siméoni +4
This work investigates learning pixel-wise semantic image segmentation in urban scenes without any manual annotation, just from the raw non-curated data collected by cars which, eq…