29 citations · 33 across the 12 of their papers we have counts for
5 papers · 1 filter
LVMT: Video Mask Transformer for Long-term Video Segmentation
Narges Norouzi, Niccol`o Cavagnero, Niccolò Cavagnero +4
Existing online video segmentation methods struggle to track objects in long, complex videos with long-term occlusions. We hypothesize that this limitation is caused by (i) the ina…
Towards Data-Efficient Video Pre-training with Frozen Image Foundation Models
Svetlana Orlova, Niccolò Cavagnero, Gijs Dubbelman
Video foundation models achieve strong performance across many video understanding tasks, but typically require large-scale pre-training on massive video datasets, resulting in sub…
Orion-Lite: Distilling LLM Reasoning into Efficient Vision-Only Driving Models
Jing Gu, Niccolò Cavagnero, Gijs Dubbelman
Leveraging the general world knowledge of Large Language Models (LLMs) holds significant promise for improving the ability of autonomous driving systems to handle rare and complex…
PMT: Plain Mask Transformer for Image and Video Segmentation with Frozen Vision Encoders
Niccolò Cavagnero, Narges Norouzi, Gijs Dubbelman +1
Vision Foundation Models (VFMs) pre-trained at scale enable a single frozen encoder to serve multiple downstream tasks simultaneously. Recent VFM-based encoder-only models for imag…
VidEoMT: Your ViT is Secretly Also a Video Segmentation Model
Narges Norouzi, Idil Esen Zulfikar, Niccolò Cavagnero +4
Existing online video segmentation models typically combine a per-frame segmenter with complex specialized tracking modules. While effective, these modules introduce significant ar…