4 citations · 6 across the 24 of their papers we have counts for
25 papers
GenPrior: Unleashing Text-to-Motion Generative Priors for Zero-Shot Skeleton-based Action Recognition
Jidong Kuang, Hongsong Wang, Jie Gui
Zero-shot skeleton-based action recognition (ZSAR) aims to recognize unseen action categories by aligning skeleton features with textual semantics. However, existing methods rely o…
RAID: Towards Robust AI-Generated Image Detection with Bit-Reversed Images
Renxi Cheng, Jie Gui, Hongsong Wang
The rapid advancement of image generation models has made it increasingly difficult for people to distinguish AI-generated images from real ones. To prevent the potential risks ass…
Retrieval-Driven Training-Free AI-Generated Video Attribution
Renxi Cheng, Chaolei Han, Jie Gui +1
AI-generated videos are becoming increasingly realistic and difficult to distinguish from authentic ones, which facilitates malicious misuse and poses growing threats to cybersecur…
Revealing Artifacts via Noise Amplification: A Novel Perspective for AI-Generated Video Detection
Renxi Cheng, Jie Gui, Hongsong Wang
With the rapid advancement of video generation models, distinguishing between AI-generated and authentic videos has emerged as a challenging endeavor. The majority of existing rese…
Property-Informed Diffusion-Based Text-to-Microstructure Generation
Bingxuan Dai, Hongsong Wang, Jie Gui
Designing 3D metamaterial microstructures that meet the intended functions remains a major challenge, as it typically requires domain expertise, iterative simulations, and extensiv…
BitC-3DGS: High-Capacity 3D Gaussian Splatting Watermarking via Bit Compression
Yuquan Bi, Baosheng Yu, Yingke Lei +5
High-capacity watermarking is necessary for 3D Gaussian Splatting (3DGS) assets to embed rich information (e.g., ownership, provenance, and authentication codes), enabling reliable…
MusicDET: Zero-Shot AI-Generated Music Detection
Chaolei Han, Hongsong Wang, Jie Gui
Detecting AI-generated music is crucial for preserving artistic authenticity and preventing the misuse of generative music technologies. However, existing discriminative detectors…
When Policy Entropy Constraint Fails: Preserving Diversity in Flow-based RLHF via Perceptual Entropy
Xiaofeng Tan, Jun Liu, Bin-Bin Gao +5
RLHF is widely used to align flow-matching text-to-image models with human preferences, but often leads to severe diversity collapse after fine-tuning. In RL, diversity is often as…
OZ-TAL: Online Zero-Shot Temporal Action Localization
Chaolei Han, Hongsong Wang, Xin Gong +1
Online Temporal Action Localization (On-TAL) aims to detect the occurrence time and category of actions in untrimmed streaming videos immediately upon their completion. Recent adva…
Marrying Text-to-Motion Generation with Skeleton-Based Action Recognition
Jidong Kuang, Hongsong Wang, Jie Gui
Human action recognition and motion generation are two active research problems in human-centric computer vision, both aiming to align motion with textual semantics. However, most…
Structure-Aware Fine-Grained Gaussian Splatting for Expressive Avatar Reconstruction
Yuze Su, Hongsong Wang, Jie Gui +1
Reconstructing photorealistic and topology-aware human avatars from monocular videos remains a significant challenge in the fields of computer vision and graphics. While existing 3…
Not All Agents Matter: From Global Attention Dilution to Risk-Prioritized Game Planning
Kang Ding, Hongsong Wang, Jie Gui +1
End-to-end autonomous driving resides not in the integration of perception and planning, but rather in the dynamic multi-agent game within a unified representation space. Most exis…
Toward Universal Skeleton-Based Action Recognition across Heterogeneous Skeletons and Open Vocabularies
Jidong Kuang, Hongsong Wang, Jie Gui +2
Skeleton data used for action recognition are acquired from a wide range of sources, including depth sensors, marker-based motion capture systems, and 2D/3D pose estimators. These…
Attribution as Retrieval: Model-Agnostic AI-Generated Image Attribution
Hongsong Wang, Renxi Cheng, Chaolei Han +1
With the rapid advancement of AIGC technologies, image forensics will encounter unprecedented challenges. Traditional methods are incapable of dealing with increasingly realistic i…
Point-Supervised Skeleton-Based Human Action Segmentation
Hongsong Wang, Yiqin Shen, Pengbo Yan +2
Skeleton-based temporal action segmentation is a fundamental yet challenging task, playing a crucial role in enabling intelligent systems to perceive and respond to human activitie…
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…
Dual Conditioned Motion Diffusion for Pose-Based Video Anomaly Detection
Hongsong Wang, Andi Xu, Pinle Ding +1
Video Anomaly Detection (VAD) is essential for computer vision research. Existing VAD methods utilize either reconstruction-based or prediction-based frameworks. The former excels…
Zero-Shot Skeleton-based Action Recognition with Dual Visual-Text Alignment
Jidong Kuang, Hongsong Wang, Chaolei Han +2
Zero-shot action recognition, which addresses the issue of scalability and generalization in action recognition and allows the models to adapt to new and unseen actions dynamically…