Human Dynamics
18 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Human Dynamics
TikTok Dataset
Latest papers
SingularTrajectory: Universal Trajectory Predictor Using Diffusion Model
In this paper, we propose SingularTrajectory, a diffusion-based universal trajectory prediction framework to reduce the performance gap across the five tasks.
Dynamic Spatial-Temporal Aggregation for Skeleton-Aware Sign Language Recognition
Current methods utilize spatial graph modules and temporal modules to capture spatial and temporal features, respectively.
InterDiff: Generating 3D Human-Object Interactions with Physics-Informed Diffusion
Sirui-Xu/InterDiff
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ICCV 2023
This paper addresses a novel task of anticipating 3D human-object interactions (HOIs).
EigenTrajectory: Low-Rank Descriptors for Multi-Modal Trajectory Forecasting
inhwanbae/eigentrajectory
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ICCV 2023
In this paper, we present EigenTrajectory ($\mathbb{ET}$), a trajectory prediction approach that uses a novel trajectory descriptor to form a compact space, known here as $\mathbb{ET}$ space, in place of Euclidean space, for representing pedestrian movements.
HabiCrowd: A High Performance Simulator for Crowd-Aware Visual Navigation
Visual navigation, a foundational aspect of Embodied AI (E-AI), has been significantly studied in the past few years.
PoseFormerV2: Exploring Frequency Domain for Efficient and Robust 3D Human Pose Estimation
However, in real scenarios, the performance of PoseFormer and its follow-ups is limited by two factors: (a) The length of the input joint sequence; (b) The quality of 2D joint detection.
D&D: Learning Human Dynamics from Dynamic Camera
jeff-sjtu/dnd
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In this work, we present D&D (Learning Human Dynamics from Dynamic Camera), which leverages the laws of physics to reconstruct 3D human motion from the in-the-wild videos with a moving camera.
RFNet-4D++: Joint Object Reconstruction and Flow Estimation from 4D Point Clouds with Cross-Attention Spatio-Temporal Features
The key insight is simultaneously performing both tasks via learning of spatial and temporal features from a sequence of point clouds can leverage individual tasks, leading to improved overall performance.
AutoAvatar: Autoregressive Neural Fields for Dynamic Avatar Modeling
facebookresearch/AutoAvatar
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In this work, for the first time, we enable autoregressive modeling of implicit avatars.
Towards Tokenized Human Dynamics Representation
likenneth/acton
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For human action understanding, a popular research direction is to analyze short video clips with unambiguous semantic content, such as jumping and drinking.
