5 papers · 1 filter
Emergence of a Shared Canonical Object Frame from In-the-Wild Videos
Tom Fischer, Martin Sundermeyer, Adam Kortylewski +1
Comparing object orientations and positions across different instances requires their poses to be expressed in a shared canonical frame. Establishing such frames has traditionally…
Hoi3DGen: Generating High-Quality Human-Object-Interactions in 3D
Agniv Sharma, Xianghui Xie, Tom Fischer +2
Modeling and generating 3D human-object interactions from text is crucial for applications in AR, XR, and gaming. Existing approaches often rely on score distillation from text-to-…
Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes
Tom Fischer, Xiaojie Zhang, Eddy Ilg
Recognizing objects in images is a fundamental problem in computer vision. Although detecting objects in 2D images is common, many applications require determining their pose in 3D…
iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental Learning
Tom Fischer, Yaoyao Liu, Artur Jesslen +6
Different from human nature, it is still common practice today for vision tasks to train deep learning models only initially and on fixed datasets. A variety of approaches have rec…
Unsupervised Learning of Category-Level 3D Pose from Object-Centric Videos
Leonhard Sommer, Artur Jesslen, Eddy Ilg +1
Category-level 3D pose estimation is a fundamentally important problem in computer vision and robotics, e.g. for embodied agents or to train 3D generative models. However, so far m…