23 citations · 70 across the 19 of their papers we have counts for
8 papers · 1 filter
HumanTOMATO: Text-aligned Whole-body Motion Generation
Shunlin Lu, Ling-Hao Chen, Ailing Zeng +4
This work targets a novel text-driven whole-body motion generation task, which takes a given textual description as input and aims at generating high-quality, diverse, and coherent…
X-Pose: Detecting Any Keypoints
Jie Yang, Ailing Zeng, Ruimao Zhang +1
This work aims to address an advanced keypoint detection problem: how to accurately detect any keypoints in complex real-world scenarios, which involves massive, messy, and open-en…
Neural Interactive Keypoint Detection
Jie Yang, Ailing Zeng, Feng Li +3
This work proposes an end-to-end neural interactive keypoint detection framework named Click-Pose, which can significantly reduce more than 10 times labeling costs of 2D keypoint a…
Motion-X: A Large-scale 3D Expressive Whole-body Human Motion Dataset
Jing Lin, Ailing Zeng, Shunlin Lu +4
In this paper, we present Motion-X, a large-scale 3D expressive whole-body motion dataset. Existing motion datasets predominantly contain body-only poses, lacking facial expression…
Boosting Human-Object Interaction Detection with Text-to-Image Diffusion Model
Jie Yang, Bingliang Li, Fengyu Yang +3
This paper investigates the problem of the current HOI detection methods and introduces DiffHOI, a novel HOI detection scheme grounded on a pre-trained text-image diffusion model,…
Inherent Consistent Learning for Accurate Semi-supervised Medical Image Segmentation
Ye Zhu, Jie Yang, Si-Qi Liu +1
Semi-supervised medical image segmentation has attracted much attention in recent years because of the high cost of medical image annotations. In this paper, we propose a novel Inh…
Semantic Human Parsing via Scalable Semantic Transfer over Multiple Label Domains
Jie Yang, Chaoqun Wang, Zhen Li +2
This paper presents Scalable Semantic Transfer (SST), a novel training paradigm, to explore how to leverage the mutual benefits of the data from different label domains (i.e. vario…
Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation
Jie Yang, Ailing Zeng, Shilong Liu +3
This paper presents a novel end-to-end framework with Explicit box Detection for multi-person Pose estimation, called ED-Pose, where it unifies the contextual learning between huma…