activity
20192022
most citedAIM 2020: Scene Relighting and Illumination Estimation Challenge

14 citations · 53 across the 13 of their papers we have counts for

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9 papers · 1 filter

cs.CV20223 cited

AIM 2022 Challenge on Instagram Filter Removal: Methods and Results

Furkan Kınlı, Sami Menteş, Barış Özcan +30

This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal. Social media filters transform the images by consecutive non-linear operations,…

cs.CV20213 cited

Improving Binary Neural Networks through Fully Utilizing Latent Weights

Weixiang Xu, Qiang Chen, Xiangyu He +2

Binary Neural Networks (BNNs) rely on a real-valued auxiliary variable W to help binary training. However, pioneering binary works only use W to accumulate gradient updates during…

cs.CV20211 cited

IntraLoss: Further Margin via Gradient-Enhancing Term for Deep Face Recognition

Chengzhi Jiang, Yanzhou Su, Wen Wang +3

Existing classification-based face recognition methods have achieved remarkable progress, introducing large margin into hypersphere manifold to learn discriminative facial represen…

cs.CV20217 cited

You Only Look One-level Feature

Qiang Chen, Yingming Wang, Tong Yang +3

This paper revisits feature pyramids networks (FPN) for one-stage detectors and points out that the success of FPN is due to its divide-and-conquer solution to the optimization pro…

cs.CV202014 cited

AIM 2020: Scene Relighting and Illumination Estimation Challenge

Majed El Helou, Ruofan Zhou, Sabine Süsstrunk +34

We review the AIM 2020 challenge on virtual image relighting and illumination estimation. This paper presents the novel VIDIT dataset used in the challenge and the different propos…

cs.CV2020

TTPP: Temporal Transformer with Progressive Prediction for Efficient Action Anticipation

Wen Wang, Xiaojiang Peng, Yanzhou Su +2

Video action anticipation aims to predict future action categories from observed frames. Current state-of-the-art approaches mainly resort to recurrent neural networks to encode hi…