Search Results for author:
Found 9 papers, 6 papers with code
Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation
We propose Hydra-MDP, a novel paradigm employing multiple teachers in a teacher-student model.
SemGrasp: Semantic Grasp Generation via Language Aligned Discretization
We introduce a discrete representation that aligns the grasp space with semantic space, enabling the generation of grasp postures in accordance with language instructions.
OAKINK2: A Dataset of Bimanual Hands-Object Manipulation in Complex Task Completion
Based on the 3-level abstraction of OAKINK2, we explore a task-oriented framework for Complex Task Completion (CTC).
CHORD: Category-level Hand-held Object Reconstruction via Shape Deformation
This can be attributed to the fact that humans have mastered the shape prior of the 'mug' category, and can quickly establish the corresponding relations between different mug instances and the prior, such as where the rim and handle are located.
Color-NeuS: Reconstructing Neural Implicit Surfaces with Color
Mesh is extracted from the signed distance function (SDF) network for the surface, and color for each surface vertex is drawn from the global color network.
DART: Articulated Hand Model with Diverse Accessories and Rich Textures
Unity GUI is also provided to generate synthetic hand data with user-defined settings, e. g., pose, camera, background, lighting, textures, and accessories.
OakInk: A Large-scale Knowledge Repository for Understanding Hand-Object Interaction
We start to collect 1, 800 common household objects and annotate their affordances to construct the first knowledge base: Oak.
ArtiBoost: Boosting Articulated 3D Hand-Object Pose Estimation via Online Exploration and Synthesis
In contrast, data synthesis can easily ensure those diversities separately.
Ranked #3 on
hand-object pose
on HO-3D v2
(using extra training data)
CPF: Learning a Contact Potential Field to Model the Hand-Object Interaction
In this paper, we present an explicit contact representation namely Contact Potential Field (CPF), and a learning-fitting hybrid framework namely MIHO to Modeling the Interaction of Hand and Object.
