Jindong Gu* — accepted AI-conference papers

2024

Dataset Distillation by Automatic Training Trajectories

Dai Liu*, Jindong Gu*, Hu Cao, Carsten Trinitis, Martin Schulz*

ECCV 2024poster

"Dataset Distillation is used to create a concise, yet informative, synthetic dataset that can replace the original dataset for training purposes. Some leading methods in this domain prioritize long-range matching, involving the unrolling of training trajectories with a fixed number of steps (NS ) o…

Cited by 14 Source ↗PDF ↗code ↗Scholar ↗

2024

Which Model Generated This Image? A Model-Agnostic Approach for Origin Attribution

Fengyuan Liu, Haochen Luo, Yiming Li, Philip Torr, Jindong Gu*

ECCV 2024poster

"Recent progress in visual generative models enables the generation of high-quality images. To prevent the misuse of generated images, it is important to identify the origin model that generates them. In this work, we study the origin attribution of generated images in a practical setting where only…

Cited by 5 Source ↗PDF ↗code ↗Scholar ↗