Real-275

The 'REAL-275' dataset is a benchmark that contains a diverse set of objects and scenes used to evaluate open-vocabulary 6D object pose estimation methods.

Papers using Real-275 (5)

MemPose: Category-level Object Pose Estimation with Memory2026TriCons-Pose: Triangle-Invariant Geometric Consistency Learning for Category-Level Object Pose Estimation2026Joint Learning of Pose Regression and Denoising Diffusion with Score Scaling Sampling for Category-level 6D Pose Estimation2025Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes2025CleanPose: Category-Level Object Pose Estimation via Causal Learning and Knowledge Distillation2025