Deep learning-based human pose estimation: A survey

C Zheng, W Wu, C Chen, T Yang, S Zhu, J Shen… - ACM Computing …, 2023 - dl.acm.org
Human pose estimation aims to locate the human body parts and build human body
representation (eg, body skeleton) from input data such as images and videos. It has drawn …

Human motion generation: A survey

W Zhu, X Ma, D Ro, H Ci, J Zhang, J Shi… - … on Pattern Analysis …, 2023 - ieeexplore.ieee.org
Human motion generation aims to generate natural human pose sequences and shows
immense potential for real-world applications. Substantial progress has been made recently …

Motiondiffuse: Text-driven human motion generation with diffusion model

M Zhang, Z Cai, L Pan, F Hong, X Guo, L Yang… - arxiv preprint arxiv …, 2022 - arxiv.org
Human motion modeling is important for many modern graphics applications, which typically
require professional skills. In order to remove the skill barriers for laymen, recent motion …

Interdiff: Generating 3d human-object interactions with physics-informed diffusion

S Xu, Z Li, YX Wang, LY Gui - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
This paper addresses a novel task of anticipating 3D human-object interactions (HOIs). Most
existing research on HOI synthesis lacks comprehensive whole-body interactions with …

Tm2t: Stochastic and tokenized modeling for the reciprocal generation of 3d human motions and texts

C Guo, X Zuo, S Wang, L Cheng - European Conference on Computer …, 2022 - Springer
Inspired by the strong ties between vision and language, the two intimate human sensing
and communication modalities, our paper aims to explore the generation of 3D human full …

Behave: Dataset and method for tracking human object interactions

BL Bhatnagar, X **e, IA Petrov… - Proceedings of the …, 2022 - openaccess.thecvf.com
Modelling interactions between humans and objects in natural environments is central to
many applications including gaming, virtual and mixed reality, as well as human behavior …

Space-time-separable graph convolutional network for pose forecasting

T Sofianos, A Sampieri, L Franco… - Proceedings of the …, 2021 - openaccess.thecvf.com
Human pose forecasting is a complex structured-data sequence-modelling task, which has
received increasing attention, also due to numerous potential applications. Research has …

From goals, waypoints & paths to long term human trajectory forecasting

K Mangalam, Y An, H Girase… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
Human trajectory forecasting is an inherently multimodal problem. Uncertainty in future
trajectories stems from two sources:(a) sources that are known to the agent but unknown to …

Trace and pace: Controllable pedestrian animation via guided trajectory diffusion

D Rempe, Z Luo, X Bin Peng, Y Yuan… - Proceedings of the …, 2023 - openaccess.thecvf.com
We introduce a method for generating realistic pedestrian trajectories and full-body
animations that can be controlled to meet user-defined goals. We draw on recent advances …

Multimodal trajectory prediction conditioned on lane-graph traversals

N Deo, E Wolff, O Beijbom - Conference on Robot Learning, 2022 - proceedings.mlr.press
Accurately predicting the future motion of surrounding vehicles requires reasoning about the
inherent uncertainty in driving behavior. This uncertainty can be loosely decoupled into …