23 citations · 70 across the 19 of their papers we have counts for
19 papers
WeThink: Toward General-purpose Vision-Language Reasoning via Reinforcement Learning
Jie Yang, Feipeng Ma, Zitian Wang +4
Building on the success of text-based reasoning models like DeepSeek-R1, extending these capabilities to multimodal reasoning holds great promise. While recent works have attempted…
Unlock the Power of Unlabeled Data in Language Driving Model
Chaoqun Wang, Jie Yang, Xiaobin Hong +1
Recent Vision-based Large Language Models~(VisionLLMs) for autonomous driving have seen rapid advancements. However, such promotion is extremely dependent on large-scale high-quali…
Semantic-Supervised Spatial-Temporal Fusion for LiDAR-based 3D Object Detection
Chaoqun Wang, Xiaobin Hong, Wenzhong Li +1
LiDAR-based 3D object detection presents significant challenges due to the inherent sparsity of LiDAR points. A common solution involves long-term temporal LiDAR data to densify th…
Motion-X++: A Large-Scale Multimodal 3D Whole-body Human Motion Dataset
Yuhong Zhang, Jing Lin, Ailing Zeng +7
In this paper, we introduce Motion-X++, a large-scale multimodal 3D expressive whole-body human motion dataset. Existing motion datasets predominantly capture body-only poses, lack…
ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model
Shunlin Lu, Jingbo Wang, Zeyu Lu +6
The scaling law has been validated in various domains, such as natural language processing (NLP) and massive computer vision tasks; however, its application to motion generation re…
KptLLM: Unveiling the Power of Large Language Model for Keypoint Comprehension
Jie Yang, Wang Zeng, Sheng Jin +4
Recent advancements in Multimodal Large Language Models (MLLMs) have greatly improved their abilities in image understanding. However, these models often struggle with grasping pix…
F-HOI: Toward Fine-grained Semantic-Aligned 3D Human-Object Interactions
Jie Yang, Xuesong Niu, Nan Jiang +2
Existing 3D human object interaction (HOI) datasets and models simply align global descriptions with the long HOI sequence, while lacking a detailed understanding of intermediate s…
Open-World Human-Object Interaction Detection via Multi-modal Prompts
Jie Yang, Bingliang Li, Ailing Zeng +2
In this paper, we develop \textbf{MP-HOI}, a powerful Multi-modal Prompt-based HOI detector designed to leverage both textual descriptions for open-set generalization and visual ex…
MotionLLM: Understanding Human Behaviors from Human Motions and Videos
Ling-Hao Chen, Shunlin Lu, Ailing Zeng +4
This study delves into the realm of multi-modality (i.e., video and motion modalities) human behavior understanding by leveraging the powerful capabilities of Large Language Models…
Toward Accurate Camera-based 3D Object Detection via Cascade Depth Estimation and Calibration
Chaoqun Wang, Yiran Qin, Zijian Kang +2
Recent camera-based 3D object detection is limited by the precision of transforming from image to 3D feature spaces, as well as the accuracy of object localization within the 3D sp…
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…
Toward Unpaired Multi-modal Medical Image Segmentation via Learning Structured Semantic Consistency
Jie Yang, Ye Zhu, Chaoqun Wang +2
Integrating multi-modal data to promote medical image analysis has recently gained great attention. This paper presents a novel scheme to learn the mutual benefits of different mod…