3 citations · 3 across the 5 of their papers we have counts for
10 papers · 1 filter
BenchSeg: A Large-Scale Dataset and Benchmark for Multi-View Food Video Segmentation
Ahmad AlMughrabi, Guillermo Rivo, Carlos Jiménez-Farfán +6
Food image segmentation is a critical task for dietary analysis, enabling accurate estimation of food volume and nutrients. However, current methods suffer from limited multi-view…
GCE-Pose: Global Context Enhancement for Category-level Object Pose Estimation
Weihang Li, Hongli Xu, Junwen Huang +4
A key challenge in model-free category-level pose estimation is the extraction of contextual object features that generalize across varying instances within a specific category. Re…
SCRREAM : SCan, Register, REnder And Map:A Framework for Annotating Accurate and Dense 3D Indoor Scenes with a Benchmark
HyunJun Jung, Weihang Li, Shun-Cheng Wu +8
Traditionally, 3d indoor datasets have generally prioritized scale over ground-truth accuracy in order to obtain improved generalization. However, using these datasets to evaluate…
Deformable 3D Gaussian Splatting for Animatable Human Avatars
HyunJun Jung, Nikolas Brasch, Jifei Song +5
Recent advances in neural radiance fields enable novel view synthesis of photo-realistic images in dynamic settings, which can be applied to scenarios with human animation. Commonl…
Polarimetric Information for Multi-Modal 6D Pose Estimation of Photometrically Challenging Objects with Limited Data
Patrick Ruhkamp, Daoyi Gao, HyunJun Jung +2
6D pose estimation pipelines that rely on RGB-only or RGB-D data show limitations for photometrically challenging objects with e.g. textureless surfaces, reflections or transparenc…
Multi-Modal Dataset Acquisition for Photometrically Challenging Object
HyunJun Jung, Patrick Ruhkamp, Nassir Navab +1
This paper addresses the limitations of current datasets for 3D vision tasks in terms of accuracy, size, realism, and suitable imaging modalities for photometrically challenging ob…