WAPR: A Foundation Model for Wide-Angle Refinement in Unseen Object Pose Estimation
cs.CV, cs.AI, cs.RO
Submitted: 2026-10-07
Updated: 2026-10-07
Comments: Accepted to ECCV 2026. 19 pages, 4 figures. Yulin Wang and Mengting Hu contributed equally. Corresponding author: Chen Luo
Journal ref: In: Computer Vision - ECCV 2026, LNCS vol. 17016, pp. 221-239. Springer, Cham (2026)
DOI: 10.1007/978-3-032-37383-0_13
Code: https://github.com/WangYuLin-SEU/WAPR
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Accurate and efficient zero-shot 6D pose estimation with frozen foundation models
- MUSE: Model-based Uncertainty-aware Similarity Estimation for zero-shot 2D Object Detection and Segmentation
- BlenderProc
- YOLOX: Exceeding YOLO Series in 2021
- Adapting Pre-Trained Vision Models for Novel Instance Detection and Segmentation
Related papers
- Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
- AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
- Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
- MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
- TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
- A Survey on Efficient Vision-Language-Action Models