20 citations · 24 across the 9 of their papers we have counts for
9 papers
Protecting Your Video Content: Disrupting Automated Video-based LLM Annotations
Haitong Liu, Kuofeng Gao, Yang Bai +4
Recently, video-based large language models (video-based LLMs) have achieved impressive performance across various video comprehension tasks. However, this rapid advancement raises…
Diffusion Prior Interpolation for Flexibility Real-World Face Super-Resolution
Jiarui Yang, Tao Dai, Yufei Zhu +3
Diffusion models represent the state-of-the-art in generative modeling. Due to their high training costs, many works leverage pre-trained diffusion models' powerful representations…
Video Watermarking: Safeguarding Your Video from (Unauthorized) Annotations by Video-based LLMs
Jinmin Li, Kuofeng Gao, Yang Bai +2
The advent of video-based Large Language Models (LLMs) has significantly enhanced video understanding. However, it has also raised some safety concerns regarding data protection, a…
Generative Pre-Trained Diffusion Paradigm for Zero-Shot Time Series Forecasting
Jiarui Yang, Tao Dai, Naiqi Li +6
In recent years, generative pre-trained paradigms such as Large Language Models (LLMs) and Large Vision Models (LVMs) have achieved revolutionary advancements and widespread real-w…
Invertible Residual Rescaling Models
Jinmin Li, Tao Dai, Yaohua Zha +6
Invertible Rescaling Networks (IRNs) and their variants have witnessed remarkable achievements in various image processing tasks like image rescaling. However, we observe that IRNs…
Boundary-aware Decoupled Flow Networks for Realistic Extreme Rescaling
Jinmin Li, Tao Dai, Jingyun Zhang +5
Recently developed generative methods, including invertible rescaling network (IRN) based and generative adversarial network (GAN) based methods, have demonstrated exceptional perf…
FMM-Attack: A Flow-based Multi-modal Adversarial Attack on Video-based LLMs
Jinmin Li, Kuofeng Gao, Yang Bai +3
Despite the remarkable performance of video-based large language models (LLMs), their adversarial threat remains unexplored. To fill this gap, we propose the first adversarial atta…
MambaIR: A Simple Baseline for Image Restoration with State-Space Model
Hang Guo, Jinmin Li, Tao Dai +3
Recent years have seen significant advancements in image restoration, largely attributed to the development of modern deep neural networks, such as CNNs and Transformers. However,…
Towards Compact 3D Representations via Point Feature Enhancement Masked Autoencoders
Yaohua Zha, Huizhen Ji, Jinmin Li +5
Learning 3D representation plays a critical role in masked autoencoder (MAE) based pre-training methods for point cloud, including single-modal and cross-modal based MAE. Specifica…