9 papers
Rethinking Model Efficiency: Multi-Agent Inference with Large Models
Sixun Dong, Juhua Hu, Steven Li +2
Most vision-language models (VLMs) apply a large language model (LLM) as the decoder, where the response tokens are generated sequentially through autoregression. Therefore, the nu…
MMTok: Multimodal Coverage Maximization for Efficient Inference of VLMs
Sixun Dong, Juhua Hu, Mian Zhang +3
Vision-Language Models (VLMs) demonstrate impressive performance in understanding visual content with language instruction by converting visual inputs to vision tokens. However, re…
Customized Multiple Clustering via Multi-Modal Subspace Proxy Learning
Jiawei Yao, Qi Qian, Juhua Hu
Multiple clustering aims to discover various latent structures of data from different aspects. Deep multiple clustering methods have achieved remarkable performance by exploiting c…
SimInversion: A Simple Framework for Inversion-Based Text-to-Image Editing
Qi Qian, Haiyang Xu, Ming Yan +1
Diffusion models demonstrate impressive image generation performance with text guidance. Inspired by the learning process of diffusion, existing images can be edited according to t…
Text-Guided Mixup Towards Long-Tailed Image Categorization
Richard Franklin, Jiawei Yao, Deyang Zhong +2
In many real-world applications, the frequency distribution of class labels for training data can exhibit a long-tailed distribution, which challenges traditional approaches of tra…
SeA: Semantic Adversarial Augmentation for Last Layer Features from Unsupervised Representation Learning
Qi Qian, Yuanhong Xu, Juhua Hu
Deep features extracted from certain layers of a pre-trained deep model show superior performance over the conventional hand-crafted features. Compared with fine-tuning or linear p…
Online Zero-Shot Classification with CLIP
Qi Qian, Juhua Hu
Vision-language pre-training such as CLIP enables zero-shot transfer that can classify images according to the candidate class names. While CLIP demonstrates an impressive zero-sho…
Multi-Modal Proxy Learning Towards Personalized Visual Multiple Clustering
Jiawei Yao, Qi Qian, Juhua Hu
Multiple clustering has gained significant attention in recent years due to its potential to reveal multiple hidden structures of data from different perspectives. The advent of de…
Dual-disentangled Deep Multiple Clustering
Jiawei Yao, Juhua Hu
Multiple clustering has gathered significant attention in recent years due to its potential to reveal multiple hidden structures of the data from different perspectives. Most of mu…