Bundlesdf: Neural 6-dof tracking and 3d reconstruction of unknown objects
We present a near real-time (10Hz) method for 6-DoF tracking of an unknown object from a
monocular RGBD video sequence, while simultaneously performing neural 3D …
monocular RGBD video sequence, while simultaneously performing neural 3D …
Hoi4d: A 4d egocentric dataset for category-level human-object interaction
We present HOI4D, a large-scale 4D egocentric dataset with rich annotations, to catalyze the
research of category-level human-object interaction. HOI4D consists of 2.4 M RGB-D …
research of category-level human-object interaction. HOI4D consists of 2.4 M RGB-D …
Gpv-pose: Category-level object pose estimation via geometry-guided point-wise voting
While 6D object pose estimation has recently made a huge leap forward, most methods can
still only handle a single or a handful of different objects, which limits their applications. To …
still only handle a single or a handful of different objects, which limits their applications. To …
Gapartnet: Cross-category domain-generalizable object perception and manipulation via generalizable and actionable parts
For years, researchers have been devoted to generalizable object perception and
manipulation, where cross-category generalizability is highly desired yet underexplored. In …
manipulation, where cross-category generalizability is highly desired yet underexplored. In …
Where2explore: Few-shot affordance learning for unseen novel categories of articulated objects
Articulated object manipulation is a fundamental yet challenging task in robotics. Due to
significant geometric and semantic variations across object categories, previous …
significant geometric and semantic variations across object categories, previous …
A survey of 6dof object pose estimation methods for different application scenarios
J Guan, Y Hao, Q Wu, S Li, Y Fang - Sensors, 2024 - mdpi.com
Recently, 6DoF object pose estimation has become increasingly important for a broad range
of applications in the fields of virtual reality, augmented reality, autonomous driving, and …
of applications in the fields of virtual reality, augmented reality, autonomous driving, and …
Shapellm: Universal 3d object understanding for embodied interaction
This paper presents ShapeLLM, the first 3D Multimodal Large Language Model (LLM)
designed for embodied interaction, exploring a universal 3D object understanding with 3D …
designed for embodied interaction, exploring a universal 3D object understanding with 3D …
Hs-pose: Hybrid scope feature extraction for category-level object pose estimation
In this paper, we focus on the problem of category-level object pose estimation, which is
challenging due to the large intra-category shape variation. 3D graph convolution (3D-GC) …
challenging due to the large intra-category shape variation. 3D graph convolution (3D-GC) …
Carto: Category and joint agnostic reconstruction of articulated objects
We present CARTO, a novel approach for reconstructing multiple articulated objects from a
single stereo RGB observation. We use implicit object-centric representations and learn a …
single stereo RGB observation. We use implicit object-centric representations and learn a …
A-sdf: Learning disentangled signed distance functions for articulated shape representation
Recent work has made significant progress on using implicit functions, as a continuous
representation for 3D rigid object shape reconstruction. However, much less effort has been …
representation for 3D rigid object shape reconstruction. However, much less effort has been …