4 papers
OccAny: Generalized Unconstrained Urban 3D Occupancy
Anh-Quan Cao, Tuan-Hung Vu
Relying on in-domain annotations and precise sensor-rig priors, existing 3D occupancy prediction methods are limited in both scalability and out-of-domain generalization. While rec…
StableMTL: Repurposing Latent Diffusion Models for Multi-Task Learning from Partially Annotated Synthetic Datasets
Anh-Quan Cao, Ivan Lopes, Raoul de Charette
Multi-task learning for dense prediction is limited by the need for extensive annotation for every task, though recent works have explored training with partial task labels. Levera…
Driving on Registers
Ellington Kirby, Alexandre Boulch, Yihong Xu +11
We present DrivoR, a simple and efficient transformer-based architecture for end-to-end autonomous driving. Our approach builds on pretrained Vision Transformers (ViTs) and introdu…
LatteCLIP: Unsupervised CLIP Fine-Tuning via LMM-Synthetic Texts
Anh-Quan Cao, Maximilian Jaritz, Matthieu Guillaumin +2
Large-scale vision-language pre-trained (VLP) models (e.g., CLIP) are renowned for their versatility, as they can be applied to diverse applications in a zero-shot setup. However,…