Search Results for author: Daan de Geus

Found 9 papers, 5 papers with code

How to Benchmark Vision Foundation Models for Semantic Segmentation?

no code implementations18 Apr 2024 Tommie Kerssies, Daan de Geus, Gijs Dubbelman

The benchmarking setup recommended in this paper enables a performance analysis of VFMs for semantic segmentation.

Benchmarking Segmentation +1

Content-aware Token Sharing for Efficient Semantic Segmentation with Vision Transformers

1 code implementation CVPR 2023 Chenyang Lu, Daan de Geus, Gijs Dubbelman

This paper introduces Content-aware Token Sharing (CTS), a token reduction approach that improves the computational efficiency of semantic segmentation networks that use Vision Transformers (ViTs).

Computational Efficiency Segmentation +2

Off-Policy Action Anticipation in Multi-Agent Reinforcement Learning

no code implementations4 Apr 2023 Ariyan Bighashdel, Daan de Geus, Pavol Jancura, Gijs Dubbelman

Learning anticipation in Multi-Agent Reinforcement Learning (MARL) is a reasoning paradigm where agents anticipate the learning steps of other agents to improve cooperation among themselves.

Action Anticipation Multi-agent Reinforcement Learning +1

Part-aware Panoptic Segmentation

1 code implementation CVPR 2021 Daan de Geus, Panagiotis Meletis, Chenyang Lu, Xiaoxiao Wen, Gijs Dubbelman

In this work, we introduce the new scene understanding task of Part-aware Panoptic Segmentation (PPS), which aims to understand a scene at multiple levels of abstraction, and unifies the tasks of scene parsing and part parsing.

Image Segmentation Panoptic Segmentation +3

Fast Panoptic Segmentation Network

no code implementations9 Oct 2019 Daan de Geus, Panagiotis Meletis, Gijs Dubbelman

For lower resolutions of the Cityscapes dataset and for the Pascal VOC dataset, FPSNet runs at 22 and 35 frames per second, respectively.

Panoptic Segmentation Segmentation

Panoptic Segmentation with a Joint Semantic and Instance Segmentation Network

no code implementations CoRR 2019 Daan de Geus, Panagiotis Meletis, Gijs Dubbelman

For instance segmentation, a Mask R-CNN type of architecture is used, while the semantic segmentation branch is augmented with a Pyramid Pooling Module.

Instance Segmentation Panoptic Segmentation +1

Cannot find the paper you are looking for? You can Submit a new open access paper.