34 citations · 113 across the 10 of their papers we have counts for
10 papers
JarvisHub: An Open Harness for Canvas-Native Multimodal Creative Agents
Yunlong Lin, Zixu Lin, Zhaohu Xing +23
Creative AI is moving from single-step asset generation toward long-horizon multimodal production. Although recent generative models can synthesize high-quality images, videos, aud…
AdAM: Few-Shot Image Generation via Adaptation-Aware Kernel Modulation
Yunqing Zhao, Keshigeyan Chandrasegaran, Milad Abdollahzadeh +5
Few-shot image generation (FSIG) aims to learn to generate new and diverse images given few (e.g., 10) training samples. Recent work has addressed FSIG by leveraging a GAN pre-trai…
On Evaluating Adversarial Robustness of Large Vision-Language Models
Yunqing Zhao, Tianyu Pang, Chao Du +4
Large vision-language models (VLMs) such as GPT-4 have achieved unprecedented performance in response generation, especially with visual inputs, enabling more creative and adaptabl…
Exploring Incompatible Knowledge Transfer in Few-shot Image Generation
Yunqing Zhao, Chao Du, Milad Abdollahzadeh +4
Few-shot image generation (FSIG) learns to generate diverse and high-fidelity images from a target domain using a few (e.g., 10) reference samples. Existing FSIG methods select, pr…
A Recipe for Watermarking Diffusion Models
Yunqing Zhao, Tianyu Pang, Chao Du +3
Diffusion models (DMs) have demonstrated advantageous potential on generative tasks. Widespread interest exists in incorporating DMs into downstream applications, such as producing…
Few-shot Image Generation via Adaptation-Aware Kernel Modulation
Yunqing Zhao, Keshigeyan Chandrasegaran, Milad Abdollahzadeh +1
Few-shot image generation (FSIG) aims to learn to generate new and diverse samples given an extremely limited number of samples from a domain, e.g., 10 training samples. Recent wor…
FS-BAN: Born-Again Networks for Domain Generalization Few-Shot Classification
Yunqing Zhao, Ngai-Man Cheung
Conventional Few-shot classification (FSC) aims to recognize samples from novel classes given limited labeled data. Recently, domain generalization FSC (DG-FSC) has been proposed w…
Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing?
Keshigeyan Chandrasegaran, Ngoc-Trung Tran, Yunqing Zhao +1
This work investigates the compatibility between label smoothing (LS) and knowledge distillation (KD). Contemporary findings addressing this thesis statement take dichotomous stand…
A Closer Look at Few-shot Image Generation
Yunqing Zhao, Henghui Ding, Houjing Huang +1
Modern GANs excel at generating high quality and diverse images. However, when transferring the pretrained GANs on small target data (e.g., 10-shot), the generator tends to replica…
Explanation-Guided Training for Cross-Domain Few-Shot Classification
Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek +3
Cross-domain few-shot classification task (CD-FSC) combines few-shot classification with the requirement to generalize across domains represented by datasets. This setup faces chal…