186 citations · 756 across the 14 of their papers we have counts for
7 papers · 1 filter
Isometric Propagation Network for Generalized Zero-shot Learning
Lu Liu, Tianyi Zhou, Guodong Long +3
Zero-shot learning (ZSL) aims to classify images of an unseen class only based on a few attributes describing that class but no access to any training sample. A popular strategy is…
Supervision by Registration and Triangulation for Landmark Detection
Xuanyi Dong, Yi Yang, Shih-En Wei +3
We present Supervision by Registration and Triangulation (SRT), an unsupervised approach that utilizes unlabeled multi-view video to improve the accuracy and precision of landmark…
AutoHAS: Efficient Hyperparameter and Architecture Search
Xuanyi Dong, Mingxing Tan, Adams Wei Yu +3
Efficient hyperparameter or architecture search methods have shown remarkable results, but each of them is only applicable to searching for either hyperparameters (HPs) or architec…
NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search
Xuanyi Dong, Yi Yang
Neural architecture search (NAS) has achieved breakthrough success in a great number of applications in the past few years. It could be time to take a step back and analyze the goo…
Searching for A Robust Neural Architecture in Four GPU Hours
Xuanyi Dong, Yi Yang
Conventional neural architecture search (NAS) approaches are based on reinforcement learning or evolutionary strategy, which take more than 3000 GPU hours to find a good model on C…
Asymptotic Soft Filter Pruning for Deep Convolutional Neural Networks
Yang He, Xuanyi Dong, Guoliang Kang +3
Deeper and wider Convolutional Neural Networks (CNNs) achieve superior performance but bring expensive computation cost. Accelerating such over-parameterized neural network has rec…
Few-Example Object Detection with Model Communication
Xuanyi Dong, Liang Zheng, Fan Ma +2
In this paper, we study object detection using a large pool of unlabeled images and only a few labeled images per category, named "few-example object detection". The key challenge…