107 citations · 236 across the 32 of their papers we have counts for
5 papers · 1 filter
CLIP-DINOiser: Teaching CLIP a few DINO tricks for open-vocabulary semantic segmentation
Monika Wysoczańska, Oriane Siméoni, Michaël Ramamonjisoa +3
The popular CLIP model displays impressive zero-shot capabilities thanks to its seamless interaction with arbitrary text prompts. However, its lack of spatial awareness makes it un…
A Simple Recipe for Language-guided Domain Generalized Segmentation
Mohammad Fahes, Tuan-Hung Vu, Andrei Bursuc +2
Generalization to new domains not seen during training is one of the long-standing challenges in deploying neural networks in real-world applications. Existing generalization techn…
Three Pillars improving Vision Foundation Model Distillation for Lidar
Gilles Puy, Spyros Gidaris, Alexandre Boulch +5
Self-supervised image backbones can be used to address complex 2D tasks (e.g., semantic segmentation, object discovery) very efficiently and with little or no downstream supervisio…
MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments
Spyros Gidaris, Andrei Bursuc, Oriane Simeoni +4
Self-supervised learning can be used for mitigating the greedy needs of Vision Transformer networks for very large fully-annotated datasets. Different classes of self-supervised le…
RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving
Angelika Ando, Spyros Gidaris, Andrei Bursuc +3
Casting semantic segmentation of outdoor LiDAR point clouds as a 2D problem, e.g., via range projection, is an effective and popular approach. These projection-based methods usuall…