47 citations · 52 across the 12 of their papers we have counts for
12 papers
Quality-Preserving Imperceptible Adversarial Attack on Skeleton-based Human Action Recognition
Ziyi Chang, Kanglei Zhou, Xiaohui Liang +1
Adversarial attacks on skeletal human action recognition have received significant attention. However, existing methods typically introduce noise-like perturbations that degrade mo…
Physics-Based Motion Tracking of Contact-Rich Interacting Characters
Xiaotang Zhang, Ziyi Chang, Qianhui Men +1
Motion tracking has been an important technique for imitating human-like movement from large-scale datasets in physics-based motion synthesis. However, existing approaches focus on…
ART: Adaptive Relational Transformer for Pedestrian Trajectory Prediction with Temporal-Aware Relations
Ruochen Li, Ziyi Chang, Junyan Hu +3
Accurate prediction of real-world pedestrian trajectories is crucial for a wide range of robot-related applications. Recent approaches typically adopt graph-based or transformer-ba…
Motion In-Betweening for Densely Interacting Characters
Xiaotang Zhang, Ziyi Chang, Qianhui Men +1
Motion in-betweening is the problem to synthesize movement between keyposes. Traditional research focused primarily on single characters. Extending them to densely interacting char…
Real-time and Controllable Reactive Motion Synthesis via Intention Guidance
Xiaotang Zhang, Ziyi Chang, Qianhui Men +1
We propose a real-time method for reactive motion synthesis based on the known trajectory of input character, predicting instant reactions using only historical, user-controlled mo…
Large-Scale Multi-Character Interaction Synthesis
Ziyi Chang, He Wang, George Alex Koulieris +1
Generating large-scale multi-character interactions is a challenging and important task in character animation. Multi-character interactions involve not only natural interactive mo…
CADReN: Contextual Anchor-Driven Relational Network for Controllable Cross-Graphs Node Importance Estimation
Zijie Zhong, Yunhui Zhang, Ziyi Chang +1
Node Importance Estimation (NIE) is crucial for integrating external information into Large Language Models through Retriever-Augmented Generation. Traditional methods, focusing on…
Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed Gradient
Zhengzhi Lu, He Wang, Ziyi Chang +2
Recently, methods for skeleton-based human activity recognition have been shown to be vulnerable to adversarial attacks. However, these attack methods require either the full knowl…
On the Design Fundamentals of Diffusion Models: A Survey
Ziyi Chang, George Alex Koulieris, Hyung Jin Chang +1
Diffusion models are learning pattern-learning systems to model and sample from data distributions with three functional components namely the forward process, the reverse process,…
Unifying Human Motion Synthesis and Style Transfer with Denoising Diffusion Probabilistic Models
Ziyi Chang, Edmund J. C. Findlay, Haozheng Zhang +1
Generating realistic motions for digital humans is a core but challenging part of computer animations and games, as human motions are both diverse in content and rich in styles. Wh…
3D Reconstruction of Sculptures from Single Images via Unsupervised Domain Adaptation on Implicit Models
Ziyi Chang, George Alex Koulieris, Hubert P. H. Shum
Acquiring the virtual equivalent of exhibits, such as sculptures, in virtual reality (VR) museums, can be labour-intensive and sometimes infeasible. Deep learning based 3D reconstr…
Denoising Diffusion Probabilistic Models for Styled Walking Synthesis
Edmund J. C. Findlay, Haozheng Zhang, Ziyi Chang +1
Generating realistic motions for digital humans is time-consuming for many graphics applications. Data-driven motion synthesis approaches have seen solid progress in recent years t…