40 citations · 132 across the 19 of their papers we have counts for
20 papers
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,…
AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Xin Li +49
This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compress…
APRIL: Finding the Achilles' Heel on Privacy for Vision Transformers
Jiahao Lu, Xi Sheryl Zhang, Tianli Zhao +2
Federated learning frameworks typically require collaborators to share their local gradient updates of a common model instead of sharing training data to preserve privacy. However,…
DPNAS: Neural Architecture Search for Deep Learning with Differential Privacy
Anda Cheng, Jiaxing Wang, Xi Sheryl Zhang +3
Training deep neural networks (DNNs) for meaningful differential privacy (DP) guarantees severely degrades model utility. In this paper, we demonstrate that the architecture of DNN…
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…
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…
HIH: Towards More Accurate Face Alignment via Heatmap in Heatmap
Xing Lan, Qinghao Hu, Qiang Chen +2
Heatmap-based regression overcomes the lack of spatial and contextual information of direct coordinate regression, and has revolutionized the task of face alignment. Yet it suffers…
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…
Multi-Faceted Representation Learning with Hybrid Architecture for Time Series Classification
Zhenyu Liu, Jian Cheng
Time series classification problems exist in many fields and have been explored for a couple of decades. However, they still remain challenging, and their solutions need to be furt…
AIM 2020 Challenge on Rendering Realistic Bokeh
Andrey Ignatov, Radu Timofte, Ming Qian +32
This paper reviews the second AIM realistic bokeh effect rendering challenge and provides the description of the proposed solutions and results. The participating teams were solvin…
Taking Modality-free Human Identification as Zero-shot Learning
Zhizhe Liu, Xingxing Zhang, Zhenfeng Zhu +3
Human identification is an important topic in event detection, person tracking, and public security. There have been numerous methods proposed for human identification, such as fac…
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…
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
Kai Zhang, Martin Danelljan, Yawei Li +75
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an in…
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…
From Anchor Generation to Distribution Alignment: Learning a Discriminative Embedding Space for Zero-Shot Recognition
Fuzhen Li, Zhenfeng Zhu, Xingxing Zhang +2
In zero-shot learning (ZSL), the samples to be classified are usually projected into side information templates such as attributes. However, the irregular distribution of templates…
A Comprehensive Study on Temporal Modeling for Online Action Detection
Wen Wang, Xiaojiang Peng, Yu Qiao +1
Online action detection (OAD) is a practical yet challenging task, which has attracted increasing attention in recent years. A typical OAD system mainly consists of three modules:…
Edge Heuristic GAN for Non-uniform Blind Deblurring
Shuai Zheng, Zhenfeng Zhu, Jian Cheng +2
Non-uniform blur, mainly caused by camera shake and motions of multiple objects, is one of the most common causes of image quality degradation. However, the traditional blind deblu…
The General Pair-based Weighting Loss for Deep Metric Learning
Haijun Liu, Jian Cheng, Wen Wang +1
Deep metric learning aims at learning the distance metric between pair of samples, through the deep neural networks to extract the semantic feature embeddings where similar samples…
Attention: A Big Surprise for Cross-Domain Person Re-Identification
Haijun Liu, Jian Cheng, Shiguang Wang +1
In this paper, we focus on model generalization and adaptation for cross-domain person re-identification (Re-ID). Unlike existing cross-domain Re-ID methods, leveraging the auxilia…
Semi-supervised Learning with Contrastive Predicative Coding
Jiaxing Wang, Yin Zheng, Xiaoshuang Chen +2
Semi-supervised learning (SSL) provides a powerful framework for leveraging unlabeled data when labels are limited or expensive to obtain. SSL algorithms based on deep neural netwo…