arXiv Computer Vision
KASALv2: Fully Automatic 3D Rotational Symmetry Classification and Axis Localization
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
Related stories
arXiv Computer Vision
Aug 26
DLTPose: 6DoF Pose Estimation From Accurate Dense Surface Point Estimates
arXiv:2504.07335v4 Announce Type: replace Abstract: We propose DLTPose, a novel method for 6DoF object pose estimation from RGBD images that combines the accuracy of sparse keypoint methods with the...
arXiv Computer Vision
1d ago
WAPR: A Foundation Model for Wide-Angle Refinement in Unseen Object Pose Estimation
WAPR is a zero‑shot wide‑angle pose refinement model that can correct candidate 6D poses with rotational errors up to 90°, achieving fast inference (≤1 s per frame) and high throughput (≈25 detections per second). It leverages rotational symmetry priors to canonicalize pose targets and introduces the SA6D dataset, which augments 944 GSO scans into ~50 k object instances and ~2 M RGB‑D images. Experiments on seven BOP core datasets demonstrate that WAPR sets new state‑of‑the‑art performance for unseen‑object pose estimation in both fast and unconstrained settings.
arXiv Computer Vision
Aug 28
A Geometry-Driven, Framework-Agnostic Optimization for Object Pose Estimation
The paper proposes a data‑centric optimization for object pose estimation that uses a physically grounded rotation representation based on principal axes alignment. By aligning an object's coordinate system with its inertial principal axes, the method achieves inherent stability, symmetry‑aware canonicalization, and framework agnosticism, allowing it to be applied at the dataset level without modifying existing networks. Experiments on category‑level and instance‑level models show consistent accuracy improvements while preserving baseline network integrity.
arXiv Machine Learning
Jul 8
Partial Symmetry Detection for 3D Geometry using Contrastive Learning with Geodesic Point Cloud Patches
arXiv:2312. 08230v2 Announce Type: replace-cross Abstract: Detecting partial extrinsic symmetry in 3D geometry is a fundamental yet persistent challenge in computer vision and graphics, critical for tasks ranging from shape completion to procedural generation.
arXiv Computer Vision
Sep 2
On the Role of Rotation Equivariance in Monocular 2D-to-3D Human Pose Lifting
arXiv:2601.13913v3 Announce Type: replace Abstract: We consider monocular 3D human pose estimation (HPE), where the goal is to predict 3D human skeletal joints from a single 2D image, typically via 2...
arXiv Computer Vision
Sep 2
Efficient and Robust Absolute Pose Estimation via Gravity-Prior-Driven Transformation Decoupling and Pose Refinement
arXiv:2609.00713v1 Announce Type: new Abstract: Estimation of the absolute pose of an object is an essential task for various robotic applications. Recently, incorporating gravity direction as prior...