collaborators

5 papers

cs.CV2026

ATSS: Detecting AI-Generated Videos via Anomalous Temporal Self-Similarity

Hang Wang, Chao Shen, Lei Zhang +1

AI-generated videos (AIGVs) have achieved unprecedented photorealism, posing severe threats to digital forensics. Existing AIGV detectors focus mainly on localized artifacts or sho…

cs.CV2024

Emphasizing Discriminative Features for Dataset Distillation in Complex Scenarios

Kai Wang, Zekai Li, Zhi-Qi Cheng +6

Dataset distillation has demonstrated strong performance on simple datasets like CIFAR, MNIST, and TinyImageNet but struggles to achieve similar results in more complex scenarios.…

cs.CV2024

Combo: Co-speech holistic 3D human motion generation and efficient customizable adaptation in harmony

Chao Xu, Mingze Sun, Zhi-Qi Cheng +5

In this paper, we propose a novel framework, Combo, for harmonious co-speech holistic 3D human motion generation and efficient customizable adaption. In particular, we identify tha…

cs.AI2024

SHIELD: LLM-Driven Schema Induction for Predictive Analytics in EV Battery Supply Chain Disruptions

Zhi-Qi Cheng, Yifei Dong, Aike Shi +5

The electric vehicle (EV) battery supply chain's vulnerability to disruptions necessitates advanced predictive analytics. We present SHIELD (Schema-based Hierarchical Induction for…

cs.LG2024

Prioritize Alignment in Dataset Distillation

Zekai Li, Ziyao Guo, Wangbo Zhao +8

Dataset Distillation aims to compress a large dataset into a significantly more compact, synthetic one without compromising the performance of the trained models. To achieve this,…