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Found 7 papers, 1 papers with code
Chronologically Accurate Retrieval for Temporal Grounding of Motion-Language Models
To achieve better temporal alignment between text and motion, we further propose to use these texts with shuffled sequence of events as negative samples during training to reinforce the motion-language models.
Exploring Vision Transformers for 3D Human Motion-Language Models with Motion Patches
To build a cross-modal latent space between 3D human motion and language, acquiring large-scale and high-quality human motion data is crucial.
Role-Aware Interaction Generation from Textual Description
We claim that certain interactions, which we call asymmetric interactions, involve a relationship between an actor and a receiver, whose motions significantly differ depending on the assigned role.
Ranked #6 on
Motion Synthesis
on InterHuman
A Closer Look at Rotation-Invariant Deep Point Cloud Analysis
Recent progress in rotation-invariant point cloud analysis is mainly driven by converting point clouds into their respective canonical poses, and principal component analysis (PCA) is a practical tool to achieve this.
Generalized Shuffled Linear Regression
Therefore, in this work, we generalize the formulation of shuffled linear regression to a broader range of conditions where only part of the data should correspond.
Neural Implicit Embedding for Point Cloud Analysis
One neural network is used to embed a portion of the distance field around a point.
Canonical and Compact Point Cloud Representation for Shape Classification
We present a novel compact point cloud representation that is inherently invariant to scale, coordinate change and point permutation.
