3 papers
cs.CV2024
BEARD: Benchmarking the Adversarial Robustness for Dataset Distillation
Zheng Zhou, Wenquan Feng, Shuchang Lyu +3
Dataset Distillation (DD) is an emerging technique that compresses large-scale datasets into significantly smaller synthesized datasets while preserving high test performance and e…
cs.CV2024
BACON: Bayesian Optimal Condensation Framework for Dataset Distillation
Zheng Zhou, Hongbo Zhao, Guangliang Cheng +4
Dataset Distillation (DD) aims to distill knowledge from extensive datasets into more compact ones while preserving performance on the test set, thereby reducing storage costs and…
cs.CV2023
OV-VG: A Benchmark for Open-Vocabulary Visual Grounding
Chunlei Wang, Wenquan Feng, Xiangtai Li +5
Open-vocabulary learning has emerged as a cutting-edge research area, particularly in light of the widespread adoption of vision-based foundational models. Its primary objective is…