18 papers
Replay-Free Continual Low-Rank Adaptation with Dynamic Memory
Huancheng Chen, Jingtao Li, Weiming Zhuang +2
We revisit continual learning~(CL), which enables pre-trained vision transformers (ViTs) to sequentially fine-tune on new downstream tasks over time. However, as the scale of these…
UniCompress: Token Compression for Unified Vision-Language Understanding and Generation
Ziyao Wang, Chen Chen, Jingtao Li +4
Unified models aim to support both understanding and generation by encoding images into discrete tokens and processing them alongside text within a single autoregressive framework.…
EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations
Jie Ren, Yingqian Cui, Chen Chen +3
Generative models, especially text-to-image diffusion models, have significantly advanced in their ability to generate images, benefiting from enhanced architectures, increased com…
DD-Ranking: Rethinking the Evaluation of Dataset Distillation
Zekai Li, Xinhao Zhong, Samir Khaki +49
In recent years, dataset distillation has provided a reliable solution for data compression, where models trained on the resulting smaller synthetic datasets achieve performance co…
Seeing Further on the Shoulders of Giants: Knowledge Inheritance for Vision Foundation Models
Jiabo Huang, Chen Chen, Lingjuan Lyu
Vision foundation models (VFMs) are predominantly developed using data-centric methods. These methods require training on vast amounts of data usually with high-quality labels, whi…
FEDEXCHANGE: Bridging the Domain Gap in Federated Object Detection for Free
Haolin Yuan, Jingtao Li, Weiming Zhuang +2
Federated Object Detection (FOD) enables clients to collaboratively train a global object detection model without accessing their local data from diverse domains. However, signific…