most citedMotionVideoGAN: A Novel Video Generator Based on the Motion Space Learned from Image Pairs

10 citations · 17 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20245 cited

PIP: Detecting Adversarial Examples in Large Vision-Language Models via Attention Patterns of Irrelevant Probe Questions

Yudong Zhang, Ruobing Xie, Jiansheng Chen +2

Large Vision-Language Models (LVLMs) have demonstrated their powerful multimodal capabilities. However, they also face serious safety problems, as adversaries can induce robustness…

cs.CV20241 cited

Strictly-ID-Preserved and Controllable Accessory Advertising Image Generation

Youze Xue, Binghui Chen, Yifeng Geng +3

Customized generative text-to-image models have the ability to produce images that closely resemble a given subject. However, in the context of generating advertising images for e-…

cs.LG2024

Advancing Out-of-Distribution Detection through Data Purification and Dynamic Activation Function Design

Yingrui Ji, Yao Zhu, Zhigang Li +3

In the dynamic realms of machine learning and deep learning, the robustness and reliability of models are paramount, especially in critical real-world applications. A fundamental c…

cs.CV2023

Few-shot 3D Shape Generation

Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1

Realistic and diverse 3D shape generation is helpful for a wide variety of applications such as virtual reality, gaming, and animation. Modern generative models, such as GANs and d…

cs.CV202310 cited

MotionVideoGAN: A Novel Video Generator Based on the Motion Space Learned from Image Pairs

Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1

Video generation has achieved rapid progress benefiting from high-quality renderings provided by powerful image generators. We regard the video synthesis task as generating a seque…

cs.CV2023

Gestalt-Guided Image Understanding for Few-Shot Learning

Kun Song, Yuchen Wu, Jiansheng Chen +2

Due to the scarcity of available data, deep learning does not perform well on few-shot learning tasks. However, human can quickly learn the feature of a new category from very few…