74 citations · 255 across the 16 of their papers we have counts for
6 papers · 1 filter
Boosting Semi-Supervised Learning with Contrastive Complementary Labeling
Qinyi Deng, Yong Guo, Zhibang Yang +2
Semi-supervised learning (SSL) has achieved great success in leveraging a large amount of unlabeled data to learn a promising classifier. A popular approach is pseudo-labeling that…
Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Images
Bingna Xu, Yong Guo, Luoqian Jiang +2
Deep networks have achieved great success in image rescaling (IR) task that seeks to learn the optimal downscaled representations, i.e., low-resolution (LR) images, to reconstruct…
Text-Aware Dual Routing Network for Visual Question Answering
Luoqian Jiang, Yifan He, Jian Chen
Visual question answering (VQA) is a challenging task to provide an accurate natural language answer given an image and a natural language question about the image. It involves mul…
Pareto-aware Neural Architecture Generation for Diverse Computational Budgets
Yong Guo, Yaofo Chen, Yin Zheng +5
Designing feasible and effective architectures under diverse computational budgets, incurred by different applications/devices, is essential for deploying deep models in real-world…
Improving Fine-tuning of Self-supervised Models with Contrastive Initialization
Haolin Pan, Yong Guo, Qinyi Deng +3
Self-supervised learning (SSL) has achieved remarkable performance in pretraining the models that can be further used in downstream tasks via fine-tuning. However, these self-super…
Towards Lightweight Super-Resolution with Dual Regression Learning
Yong Guo, Mingkui Tan, Zeshuai Deng +5
Deep neural networks have exhibited remarkable performance in image super-resolution (SR) tasks by learning a mapping from low-resolution (LR) images to high-resolution (HR) images…