4 citations · 14 across the 19 of their papers we have counts for
7 papers · 1 filter
TernaryCLIP: Efficiently Compressing Vision-Language Models with Ternary Weights and Distilled Knowledge
Shu-Hao Zhang, Wei-Cheng Tang, Chen Wu +5
Recent years have witnessed an increasing interest in image-text contrastive modeling, exemplified by models such as Contrastive Language-Image Pretraining (CLIP). In this paper, w…
Physics-Driven Spatiotemporal Modeling for AI-Generated Video Detection
Shuhai Zhang, ZiHao Lian, Jiahao Yang +6
AI-generated videos have achieved near-perfect visual realism (e.g., Sora), urgently necessitating reliable detection mechanisms. However, detecting such videos faces significant c…
Test-Time Model Adaptation for Quantized Neural Networks
Zeshuai Deng, Guohao Chen, Shuaicheng Niu +6
Quantizing deep models prior to deployment is a widely adopted technique to speed up inference for various real-time applications, such as autonomous driving. However, quantized mo…
Zero-Shot Skeleton-Based Action Recognition With Prototype-Guided Feature Alignment
Kai Zhou, Shuhai Zhang, Zeng You +3
Zero-shot skeleton-based action recognition aims to classify unseen skeleton-based human actions without prior exposure to such categories during training. This task is extremely c…
HiLo: Detailed and Robust 3D Clothed Human Reconstruction with High-and Low-Frequency Information of Parametric Models
Yifan Yang, Dong Liu, Shuhai Zhang +3
Reconstructing 3D clothed human involves creating a detailed geometry of individuals in clothing, with applications ranging from virtual try-on, movies, to games. To enable practic…
Cross-Ray Neural Radiance Fields for Novel-view Synthesis from Unconstrained Image Collections
Yifan Yang, Shuhai Zhang, Zixiong Huang +2
Neural Radiance Fields (NeRF) is a revolutionary approach for rendering scenes by sampling a single ray per pixel and it has demonstrated impressive capabilities in novel-view synt…
Towards Efficient Task-Driven Model Reprogramming with Foundation Models
Shoukai Xu, Jiangchao Yao, Ran Luo +5
Vision foundation models exhibit impressive power, benefiting from the extremely large model capacity and broad training data. However, in practice, downstream scenarios may only s…