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OD3: Optimization-free Dataset Distillation for Object Detection
Salwa K. Al Khatib, Ahmed ElHagry, Shitong Shao +1
Training large neural networks on large-scale datasets requires substantial computational resources, particularly for dense prediction tasks such as object detection. Although data…
DELT: A Simple Diversity-driven EarlyLate Training for Dataset Distillation
Zhiqiang Shen, Ammar Sherif, Zeyuan Yin +1
Recent advances in dataset distillation have led to solutions in two main directions. The conventional batch-to-batch matching mechanism is ideal for small-scale datasets and inclu…
Self-supervised Dataset Distillation: A Good Compression Is All You Need
Muxin Zhou, Zeyuan Yin, Shitong Shao +1
Dataset distillation aims to compress information from a large-scale original dataset to a new compact dataset while striving to preserve the utmost degree of the original data inf…
Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching
Shitong Shao, Zeyuan Yin, Muxin Zhou +2
The lightweight "local-match-global" matching introduced by SRe2L successfully creates a distilled dataset with comprehensive information on the full 224x224 ImageNet-1k. However,…