4 papers
Geometric Correspondence Fields: Learned Differentiable Rendering for 3D Pose Refinement in the Wild
Alexander Grabner, Yaming Wang, Peizhao Zhang +5
We present a novel 3D pose refinement approach based on differentiable rendering for objects of arbitrary categories in the wild. In contrast to previous methods, we make two main…
Improving Annotation for 3D Pose Dataset of Fine-Grained Object Categories
Yaming Wang, Xiao Tan, Yi Yang +4
Existing 3D pose datasets of object categories are limited to generic object types and lack of fine-grained information. In this work, we introduce a new large-scale dataset that c…
3D Pose Estimation for Fine-Grained Object Categories
Yaming Wang, Xiao Tan, Yi Yang +4
Existing object pose estimation datasets are related to generic object types and there is so far no dataset for fine-grained object categories. In this work, we introduce a new lar…
Mining Discriminative Triplets of Patches for Fine-Grained Classification
Yaming Wang, Jonghyun Choi, Vlad I. Morariu +1
Fine-grained classification involves distinguishing between similar sub-categories based on subtle differences in highly localized regions; therefore, accurate localization of disc…