14 citations · 24 across the 5 of their papers we have counts for
7 papers
MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model
Zhongcong Xu, Jianfeng Zhang, Jun Hao Liew +5
This paper studies the human image animation task, which aims to generate a video of a certain reference identity following a particular motion sequence. Existing animation works t…
Towards Adversarial Robustness of Deep Vision Algorithms
Hanshu Yan
Deep learning methods have achieved great success in solving computer vision tasks, and they have been widely utilized in artificially intelligent systems for image processing, ana…
MagicMix: Semantic Mixing with Diffusion Models
Jun Hao Liew, Hanshu Yan, Daquan Zhou +1
Have you ever imagined what a corgi-alike coffee machine or a tiger-alike rabbit would look like? In this work, we attempt to answer these questions by exploring a new task called…
Towards Adversarially Robust Deep Image Denoising
Hanshu Yan, Jingfeng Zhang, Jiashi Feng +2
This work systematically investigates the adversarial robustness of deep image denoisers (DIDs), i.e, how well DIDs can recover the ground truth from noisy observations degraded by…
Recovering the Unbiased Scene Graphs from the Biased Ones
Meng-Jiun Chiou, Henghui Ding, Hanshu Yan +3
Given input images, scene graph generation (SGG) aims to produce comprehensive, graphical representations describing visual relationships among salient objects. Recently, more effo…
RAIN: A Simple Approach for Robust and Accurate Image Classification Networks
Jiawei Du, Hanshu Yan, Vincent Y. F. Tan +3
It has been shown that the majority of existing adversarial defense methods achieve robustness at the cost of sacrificing prediction accuracy. The undesirable severe drop in accura…