Recent advances in large-scale pretraining have yielded visual foundation models with
strong capabilities. Not only can recent models generalize to arbitrary images for their …

Camera pose estimation is a key step in standard 3D reconstruction pipelines that operates
on a dense set of images of a single object or scene. However, methods for pose estimation …

We introduce a new RGB-D object dataset captured in the wild called WildRGB-D. Unlike
most existing real-world object-centric datasets which only come with RGB capturing the …

Estimating the pose of an unseen object is the goal of the challenging one-shot pose
estimation task. Previous methods have heavily relied on feature matching with great …

In this letter, we introduce ViHOPE, a novel framework for estimating the 6D pose of an in-
hand object using visuotactile perception. Our key insight is that the accuracy of the 6D …

Abstract 6D object pose estimation aims at determining an object's translation, rotation, and
scale, typically from a single RGBD image. Recent advancements have expanded this …

6-D object pose estimation is widely used in the robotic grasp, and a series of object pose
estimation methods have been proposed. Among them, category-level object pose …

Recently, various methods for 6D pose and shape estimation of objects at a per-category
level have been proposed. This work provides an overview of the field in terms of methods …

Category-level 3D pose estimation is a fundamentally important problem in computer vision
and robotics eg for embodied agents or to train 3D generative models. However so far …

Object pose estimation is a fundamental computer vision problem with broad applications in
augmented reality and robotics. Over the past decade, deep learning models, due to their …