4 citations · 6 across the 24 of their papers we have counts for
7 papers · 1 filter
Multimodal Skeleton-Based Action Representation Learning via Decomposition and Composition
Hongsong Wang, Heng Fei, Bingxuan Dai +1
Multimodal human action understanding is a significant problem in computer vision, with the central challenge being the effective utilization of the complementarity among diverse m…
LOTA: Bit-Planes Guided AI-Generated Image Detection
Hongsong Wang, Renxi Cheng, Yang Zhang +2
The rapid advancement of GAN and Diffusion models makes it more difficult to distinguish AI-generated images from real ones. Recent studies often use image-based reconstruction err…
Dragging with Geometry: From Pixels to Geometry-Guided Image Editing
Xinyu Pu, Hongsong Wang, Jie Gui +1
Interactive point-based image editing serves as a controllable editor, enabling precise and flexible manipulation of image content. However, most drag-based methods operate primari…
Efficient Diffusion-Based 3D Human Pose Estimation with Hierarchical Temporal Pruning
Yuquan Bi, Hongsong Wang, Xinli Shi +3
Diffusion models have demonstrated strong capabilities in generating high-fidelity 3D human poses, yet their iterative nature and multi-hypothesis requirements incur substantial co…
Heterogeneous Skeleton-Based Action Representation Learning
Hongsong Wang, Xiaoyan Ma, Jidong Kuang +1
Skeleton-based human action recognition has received widespread attention in recent years due to its diverse range of application scenarios. Due to the different sources of human s…
Data-Free Class-Incremental Gesture Recognition with Prototype-Guided Pseudo Feature Replay
Hongsong Wang, Ao Sun, Jie Gui +1
Gesture recognition is an important research area in the field of computer vision. Most gesture recognition efforts focus on close-set scenarios, thereby limiting the capacity to e…
Training-Free Zero-Shot Temporal Action Detection with Vision-Language Models
Chaolei Han, Hongsong Wang, Jidong Kuang +2
Existing zero-shot temporal action detection (ZSTAD) methods predominantly use fully supervised or unsupervised strategies to recognize unseen activities. However, these training-b…