8 citations · 9 across the 3 of their papers we have counts for
7 papers
Human-Centric Intelligence in the Era of Foundation Models: A Survey
Yang Chen, Tianqi Wang, Xiaorui Jiang +13
Human-centric intelligence is evolving in the foundation-model era, with growing emphasis on scale, transferability, and general-purpose modeling. Yet it has not fully integrated w…
SATO: Stable Text-to-Motion Framework
Wenshuo Chen, Hongru Xiao, Erhang Zhang +4
Is the Text to Motion model robust? Recent advancements in Text to Motion models primarily stem from more accurate predictions of specific actions. However, the text modality typic…
GCNext: Towards the Unity of Graph Convolutions for Human Motion Prediction
Xinshun Wang, Qiongjie Cui, Chen Chen +1
The past few years has witnessed the dominance of Graph Convolutional Networks (GCNs) over human motion prediction.Various styles of graph convolutions have been proposed, with eac…
Expressive Forecasting of 3D Whole-body Human Motions
Pengxiang Ding, Qiongjie Cui, Min Zhang +3
Human motion forecasting, with the goal of estimating future human behavior over a period of time, is a fundamental task in many real-world applications. However, existing works ty…
Skeleton-in-Context: Unified Skeleton Sequence Modeling with In-Context Learning
Xinshun Wang, Zhongbin Fang, Xia Li +2
In-context learning provides a new perspective for multi-task modeling for vision and NLP. Under this setting, the model can perceive tasks from prompts and accomplish them without…
A Single 2D Pose with Context is Worth Hundreds for 3D Human Pose Estimation
Qitao Zhao, Ce Zheng, Mengyuan Liu +1
The dominant paradigm in 3D human pose estimation that lifts a 2D pose sequence to 3D heavily relies on long-term temporal clues (i.e., using a daunting number of video frames) for…