748 citations · 1.9k across the 32 of their papers we have counts for
52 papers
Divide, Evaluate, and Refine: Evaluating and Improving Text-to-Image Alignment with Iterative VQA Feedback
Jaskirat Singh, Liang Zheng
The field of text-conditioned image generation has made unparalleled progress with the recent advent of latent diffusion models. While remarkable, as the complexity of given text i…
Large-scale Training Data Search for Object Re-identification
Yue Yao, Huan Lei, Tom Gedeon +1
We consider a scenario where we have access to the target domain, but cannot afford on-the-fly training data annotation, and instead would like to construct an alternative training…
Adma-GAN: Attribute-Driven Memory Augmented GANs for Text-to-Image Generation
Xintian Wu, Hanbin Zhao, Liangli Zheng +2
As a challenging task, text-to-image generation aims to generate photo-realistic and semantically consistent images according to the given text descriptions. Existing methods mainl…
Hierarchical Image Classification with A Literally Toy Dataset
Long He, Dandan Song, Liang Zheng
Unsupervised domain adaptation (UDA) in image classification remains a big challenge. In existing UDA image dataset, classes are usually organized in a flattened way, where a plain…
Ranking Models in Unlabeled New Environments
Xiaoxiao Sun, Yunzhong Hou, Weijian Deng +2
Consider a scenario where we are supplied with a number of ready-to-use models trained on a certain source domain and hope to directly apply the most appropriate ones to different…
Memory-Free Generative Replay For Class-Incremental Learning
Xiaomeng Xin, Yiran Zhong, Yunzhong Hou +2
Regularization-based methods are beneficial to alleviate the catastrophic forgetting problem in class-incremental learning. With the absence of old task images, they often assume t…