no code implementations • 15 Mar 2024 • Dingding Cai, Janne Heikkilä, Esa Rahtu
At inference, GS-Pose operates sequentially by locating the object in the input image, estimating its initial 6D pose using a retrieval approach, and refining the pose with a render-and-compare method.
no code implementations • 5 Nov 2023 • Xuqian Ren, Wenjia Wang, Dingding Cai, Tuuli Tuominen, Juho Kannala, Esa Rahtu
Metaverse technologies demand accurate, real-time, and immersive modeling on consumer-grade hardware for both non-human perception (e. g., drone/robot/autonomous car navigation) and immersive technologies like AR/VR, requiring both structural accuracy and photorealism.
1 code implementation • 17 Feb 2023 • Wenyan Yang, Huiling Wang, Dingding Cai, Joni Pajarinen, Joni-Kristen Kämäräinen
Offline goal-conditioned reinforcement learning (GCRL) can be challenging due to overfitting to the given dataset.
no code implementations • 14 Feb 2023 • Dingding Cai, Janne Heikkilä, Esa Rahtu
Though massive amounts of synthetic RGB images are easy to obtain, the models trained on them suffer from noticeable performance degradation due to the synthetic-to-real domain gap.
1 code implementation • 3 Aug 2022 • Dingding Cai, Janne Heikkilä, Esa Rahtu
The pose estimation is decomposed into three sub-tasks: a) object 3D rotation representation learning and matching; b) estimation of the 2D location of the object center; and c) scale-invariant distance estimation (the translation along the z-axis) via classification.
1 code implementation • CVPR 2022 • Dingding Cai, Janne Heikkilä, Esa Rahtu
This paper proposes a universal framework, called OVE6D, for model-based 6D object pose estimation from a single depth image and a target object mask.
no code implementations • 15 Mar 2017 • Dingding Cai, Ke Chen, Yanlin Qian, Joni-Kristian Kämäräinen
Successful fine-grained image classification methods learn subtle details between visually similar (sub-)classes, but the problem becomes significantly more challenging if the details are missing due to low resolution.