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20192024
most citedSoccerNet 2022 Challenges Results

37 citations · 52 across the 9 of their papers we have counts for

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9 papers · 1 filter

cs.CV2023

Efficient Dataset Distillation via Minimax Diffusion

Jianyang Gu, Saeed Vahidian, Vyacheslav Kungurtsev +4

Dataset distillation reduces the storage and computational consumption of training a network by generating a small surrogate dataset that encapsulates rich information of the origi…

cs.CV20231 cited

DREAM+: Efficient Dataset Distillation by Bidirectional Representative Matching

Yanqing Liu, Jianyang Gu, Kai Wang +4

Dataset distillation plays a crucial role in creating compact datasets with similar training performance compared with original large-scale ones. This is essential for addressing t…

cs.CV20232 cited

Can pre-trained models assist in dataset distillation?

Yao Lu, Xuguang Chen, Yuchen Zhang +7

Dataset Distillation (DD) is a prominent technique that encapsulates knowledge from a large-scale original dataset into a small synthetic dataset for efficient training. Meanwhile,…

cs.CV20231 cited

Color Prompting for Data-Free Continual Unsupervised Domain Adaptive Person Re-Identification

Jianyang Gu, Hao Luo, Kai Wang +3

Unsupervised domain adaptive person re-identification (Re-ID) methods alleviate the burden of data annotation through generating pseudo supervision messages. However, real-world Re…

cs.CV2023

Dataset Quantization

Daquan Zhou, Kai Wang, Jianyang Gu +5

State-of-the-art deep neural networks are trained with large amounts (millions or even billions) of data. The expensive computation and memory costs make it difficult to train them…

cs.CV202237 cited

SoccerNet 2022 Challenges Results

Silvio Giancola, Anthony Cioppa, Adrien Deliège +91

The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks:…