259 citations · 283 across the 8 of their papers we have counts for
8 papers
SCP: Spatial Causal Prediction in Video
Yanguang Zhao, Jie Yang, Shengqiong Wu +9
Spatial reasoning, the ability to understand spatial relations, causality, and dynamic evolution, is central to human intelligence and essential for real-world applications such as…
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…
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…
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,…
Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
Shilong Liu, Zhaoyang Zeng, Tianhe Ren +9
In this paper, we present an open-set object detector, called Grounding DINO, by marrying Transformer-based detector DINO with grounded pre-training, which can detect arbitrary obj…
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…