37 citations · 69 across the 8 of their papers we have counts for
9 papers · 1 filter
HiLo: Exploiting High Low Frequency Relations for Unbiased Panoptic Scene Graph Generation
Zijian Zhou, Miaojing Shi, Holger Caesar
Panoptic Scene Graph generation (PSG) is a recently proposed task in image scene understanding that aims to segment the image and extract triplets of subjects, objects and their re…
SliceMatch: Geometry-guided Aggregation for Cross-View Pose Estimation
Ted Lentsch, Zimin Xia, Holger Caesar +1
This work addresses cross-view camera pose estimation, i.e., determining the 3-Degrees-of-Freedom camera pose of a given ground-level image w.r.t. an aerial image of the local area…
Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking
Whye Kit Fong, Rohit Mohan, Juana Valeria Hurtado +4
Panoptic scene understanding and tracking of dynamic agents are essential for robots and automated vehicles to navigate in urban environments. As LiDARs provide accurate illuminati…
NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles
Holger Caesar, Juraj Kabzan, Kok Seang Tan +6
In this work, we propose the world's first closed-loop ML-based planning benchmark for autonomous driving. While there is a growing body of ML-based motion planners, the lack of es…
The efficacy of Neural Planning Metrics: A meta-analysis of PKL on nuScenes
Yiluan Guo, Holger Caesar, Oscar Beijbom +2
A high-performing object detection system plays a crucial role in autonomous driving (AD). The performance, typically evaluated in terms of mean Average Precision, does not take in…
Weakly Supervised Object Localization Using Things and Stuff Transfer
Miaojing Shi, Holger Caesar, Vittorio Ferrari
We propose to help weakly supervised object localization for classes where location annotations are not available, by transferring things and stuff knowledge from a source set with…
COCO-Stuff: Thing and Stuff Classes in Context
Holger Caesar, Jasper Uijlings, Vittorio Ferrari
Semantic classes can be either things (objects with a well-defined shape, e.g. car, person) or stuff (amorphous background regions, e.g. grass, sky). While lots of classification a…
Region-based semantic segmentation with end-to-end training
Holger Caesar, Jasper Uijlings, Vittorio Ferrari
We propose a novel method for semantic segmentation, the task of labeling each pixel in an image with a semantic class. Our method combines the advantages of the two main competing…
Joint Calibration for Semantic Segmentation
Holger Caesar, Jasper Uijlings, Vittorio Ferrari
Semantic segmentation is the task of assigning a class-label to each pixel in an image. We propose a region-based semantic segmentation framework which handles both full and weak s…